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355 Commits

Author SHA1 Message Date
Nicolas Patry a70b087e71
Removing accepted ids in the regular info logs, downgrade to debug. (#1898)
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2024-05-15 13:56:07 +02:00
Daniël de Kok b5bc6e5c4e
Add GPT-2 with flash attention (#1889)
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This change adds `FlashGPT2ForCausalLM` and wires it up. The model
itself is pretty straightforward, the main difference from other models
is that it uses trained position embeddings and that all weight matrices
are transposed compared to other models (due to the use of Conv1D in the
upstream model).


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2024-05-15 13:31:22 +02:00
Nicolas Patry e3d765645a
MLPSpeculator. (#1865)
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---------

Co-authored-by: Joshua Rosenkranz <joshua.rosenkranz@gmail.com>
2024-05-14 12:33:18 +02:00
Nilabhra Roy Chowdhury 3136f27f36
Add: Support for the Falcon2 11B architecture (#1886)
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Add's support for the Falcon2 11B model architecture.


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---------

Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: oOraph <13552058+oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Julien Chaumond <julien@huggingface.co>
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
Co-authored-by: abhishek thakur <1183441+abhishekkrthakur@users.noreply.github.com>
Co-authored-by: Dong Shin <d0104.shin@gmail.com>
Co-authored-by: Christof Weickhardt <christof@weickhardt.ch>
Co-authored-by: Ikko Eltociear Ashimine <eltociear@gmail.com>
Co-authored-by: drbh <david.richard.holtz@gmail.com>
Co-authored-by: Lucain <lucain@huggingface.co>
Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
Co-authored-by: Moritz Laurer <41862082+MoritzLaurer@users.noreply.github.com>
Co-authored-by: dr3s <dr3s@users.noreply.github.com>
Co-authored-by: Wang, Yi <yi.a.wang@intel.com>
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
Co-authored-by: Maziyar Panahi <maziyar.panahi@iscpif.fr>
Co-authored-by: Brandon Royal <2762697+brandonroyal@users.noreply.github.com>
Co-authored-by: Mishig <mishig.davaadorj@coloradocollege.edu>
Co-authored-by: Martin Iglesias Goyanes <martinigoyanes@hotmail.com>
Co-authored-by: martini <martin.iglesiasgoyanes@adyen.com>
2024-05-14 10:06:02 +02:00
Nicolas Patry d348d2b28f
Granite support? (#1882)
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2024-05-13 13:46:29 +02:00
Nicolas Patry fd89d9dfae
Refactor layers. (#1866)
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2024-05-13 12:44:30 +02:00
Nicolas Patry de079d607a
Remove misleading warning (not that important nowadays anyway). (#1848)
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2024-05-02 15:09:46 +02:00
Nicolas Patry 27b3a2c9fc
Fix: "Fixing" double BOS for mistral too. (#1843)
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2024-05-01 18:21:17 +02:00
Nicolas Patry 04d4765bad
Small CI cleanup. (#1801)
# What does this PR do?

Just unifying some branches and making intentions clearer (no cuda graph
when 0 all the way in the launcher)

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2024-04-30 11:39:38 +02:00
Nicolas Patry e9f03f822a
Dummy CI run. (#1817)
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2024-04-26 19:19:55 +02:00
Nicolas Patry 8b8e8f6632
Fixing qwen2. (#1818)
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2024-04-26 19:19:08 +02:00
Nicolas Patry a8fd4236eb
Blunder (#1815)
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2024-04-26 15:51:09 +02:00
Wang, Yi 45ecf9d040
add intel xpu support for TGI (#1475)
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---------

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-04-26 15:48:58 +02:00
Nicolas Patry ee47973a2f
Use the generation config. (#1808)
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2024-04-25 19:41:50 +02:00
Nicolas Patry bfddfa5955
Idefics2. (#1756)
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2024-04-23 23:04:44 +02:00
Nicolas Patry 986b4044d1
Phi3 support (#1797)
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2024-04-23 18:40:05 +02:00
fxmarty 26b3916612
Make `--cuda-graphs` work as expected (bis) (#1768)
This was ignored up to now, even with `--cuda-graphs 0`.

With this fix, `--cuda-graphs` is obeyed to.
2024-04-22 16:09:19 +02:00
OlivierDehaene c38a7d7ddd
v2.0.0 (#1736) 2024-04-12 18:38:34 +02:00
OlivierDehaene eefea5ee31
feat: medusa v2 (#1734) 2024-04-12 16:24:45 +02:00
OlivierDehaene 30620a9a44 hotfix: mixtral 2024-04-10 18:38:08 +02:00
OlivierDehaene ad9d6288c8
fix: fix CohereForAI/c4ai-command-r-plus (#1707)
@Narsil @drbh this will update flash attention v2 and vllm.
You will need to re-install them.
2024-04-10 17:20:25 +02:00
Nicolas Patry 4634b00c2a
Adding Llava-Next (Llava 1.6) with full support. (#1709)
# What does this PR do?

- Changed all models to extract `embed_tokens` in order to enable llava
to separately call the embeddings and the core model layers.
- Added VlmCausalLM to inherit from FlashMistral in order to be
maximally supported. The only added logics sits on top and parses images
into pixel values, preallocates input_ids space for the image
embeddings, and passes them for the model.
- Added Clip for the vision tower.
- Didn't add flash for the vision tower since there's no padding anyway.
- Added heuristic (potentially incomplete) to calculate number of
features *before* calculating the clip patches (allows for easier logic
reuse of the LLM under the hood).


Still needs to be done:

- [x] Implement the image parsing in the controller side, to avoid
downloading n times per TP shard and also refusing requests too large
early and avoid issues where the truncation actually truncates the
image.
- [ ] Make sure it works with quantization properly.
- [x] Make sure it works with TP>1



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2024-04-09 21:32:00 +02:00
Nicolas Patry 106d8ee818
Automatic quantization config. (#1719)
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2024-04-09 10:27:57 +02:00
Nicolas Patry f9958ee191
Fixing cohere tokenizer. (#1697) 2024-04-05 16:44:19 +02:00
Nicolas Patry 99874eae74
Add cuda graphs sizes and make it default. (#1703)
# What does this PR do?

```
text-generation-launcher --model-id XXX # Uses cuda graphs by default
text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
```
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2024-04-04 23:01:56 +02:00
OlivierDehaene f04255c694
feat: Add dbrx support (#1685)
Close #1679
2024-03-29 18:49:36 +01:00
OlivierDehaene 1e9bcd9dd8
feat: cohere (#1660) 2024-03-22 17:59:25 +01:00
SeongBeomLEE 66914f7b19
fix: LlamaTokenizerFast to AutoTokenizer at flash_mistral.py (#1637)
# What does this PR do?

A few cases where you're using a mistral structure or mixtral structure
but not a llama tokenizer, why not make it to call the AutoTokenizer in
exception handling.

Similar PR #619

@Narsil
2024-03-22 17:13:13 +01:00
Nicolas Patry ed29d6eeab
Remove unecessary cuda graph. (#1664)
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2024-03-21 20:11:05 +01:00
drbh 6f15ac60b2
feat: support force downcast after FastRMSNorm multiply for Gemma (#1658)
This PR adds `force_downcast_after` to `FastRMSNorm.forward` which is
used in the Gemma model. References
https://github.com/huggingface/transformers/pull/29402 and
https://github.com/huggingface/transformers/pull/29729

Setting `force_downcast_after=True` will perform the `hidden_states *
weight` multiplication in f32 and then downcast to half. This differs
slightly from the current implementation which first casts the
`hidden_states` to a half and then multiples.
2024-03-21 10:25:11 +01:00
drbh 3dd7da2198
feat: accept legacy request format and response (#1527)
This WIP PR (will) add support for legacy OpenAI `v1/completions` API.

This should allow TGI to be a drop in replacement for OpenAI when using
tools that rely on the completions api

Should fix:
https://github.com/huggingface/text-generation-inference/issues/1468
2024-02-29 10:44:20 -05:00
Nicolas Patry 5a3903ba99
Fix idefics default. (#1614)
# What does this PR do?

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2024-02-29 13:16:34 +01:00
drbh 343aa7a197
fix: Handle concurrent grammar requests (#1610)
This PR fixes parallel grammar requests, currently grammar states are
not concatenated correctly when a new request is added to the batch and
this results in incorrect generation. This PR updates the `concatenate`
function to correctly include the previous states.

fixes: #1601
2024-02-29 11:17:42 +01:00
OlivierDehaene 26cdea5c0c
feat: Qwen2 (#1608)
See #1584

---------

Co-authored-by: Cheng Kuan Yong Jason <jasoncky96@gmail.com>
2024-02-28 15:50:31 +01:00
OlivierDehaene b40e833493
feat: starcoder2 (#1605) 2024-02-28 12:07:08 +01:00
Nicolas Patry bf700e7eef
Revamp medusa implementation so that every model can benefit. (#1588)
# What does this PR do?

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2024-02-26 19:49:28 +01:00
OlivierDehaene c86f58d37c
feat: add support for Gemma (#1583) 2024-02-21 14:15:22 +01:00
Nicolas Patry d19c768cb8
Fix mistral with length > window_size for long prefills (rotary doesn't create long enough cos, sin). (#1571)
# What does this PR do?

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2024-02-19 15:23:12 +01:00
OlivierDehaene 9946165ee0
chore: add pre-commit (#1569) 2024-02-16 11:58:58 +01:00
drbh cef0553d59
Outlines guided generation (#1539)
This WIP PR starts to add grammar support via outlines, currently this
PR supports very simple regex grammars and does not optimize for
precompiling or caching grammar fsm's.

todo:
- [X] add simple outlines guidance to `NextTokenChooser`
- [X] update protos for grammar
- [X] update generation params API
- [X] constrain simple grammar
- [ ] support parsing more complex grammar into fsm
- [ ] support all outline support grammar types
- [ ] explore optimizations to avoid recompiling grammars

guided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data-raw '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6,
        "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+"
    }
}' | jq
```
response
```json
{
  "generated_text": "david@example.com"
}
```

unguided request
```bash
curl -s 'http://localhost:3000/generate' \
--header 'Content-Type: application/json' \
--data '{
    "inputs": "make an email for david: \n",
    "parameters": {
        "max_new_tokens": 6
    }
}' | jq
```
response
```json
{
  "generated_text": "    email = 'david"
}
```
2024-02-15 10:28:10 +01:00
Nicolas Patry 4c2848b24b
Small cleanup. (#1560)
Using a single `os.getenv` statement instead of multiple.
Should make truthful values easier to catch

In the end didn't move towards full CLI because modifying globals in
Python is error prone (depends on code import order).

Added an error when mamba is launched with TP.


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2024-02-14 15:30:07 +01:00
Nicolas Patry d6b0fb9e25
Improving mamba runtime by using updates (#1552)
- Move float16 to bfloat16, which has less imprecisions (load test are
  failing with the update kernels + f16, all working under bf16).

  Another note, is that we are not respecting the layer norm in f32
  defined in the configuration (this is OK in my book, but that could
  impact the f16 precision)

- Moved to update kernels. Triton overhead is super high, removed by
  switching to cuda graphs works great (update cuda graph is available
  in TRT-LLM if needed, seems *exactly* like the regular ssm kernel.

- Moved inference_params struct in order to make only 2 tensors, to
  reduce the overhead of copying back and forth to the cuda graphs.

- Left over overhead seems entirely in the tokenization bit. (Still 4
  copies are paid before launching the graph)


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2024-02-14 09:54:10 +01:00
OlivierDehaene 0d794af6a5
feat: experimental support for cuda graphs (#1428)
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-02-12 10:09:29 +01:00
Ilyas Moutawwakil a4e5801684
ROCm AWQ support (#1514)
# What does this PR do?

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This PR adds the possibility to run AWQ models with Exllama/GPTQ
kernels, specifically for ROCm devices that support Exllama kernels but
not AWQ's GEMM.

This is done by :
- un-packing, reordering and re-packing AWQ weights when `--quantize
gptq` but the model's `quant_method=awq`.
- avoiding overflows when adding 1 to zeros in exllama and triton.

Ref: https://github.com/casper-hansen/AutoAWQ/pull/313

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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- [ ] Did you write any new necessary tests?


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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-02-09 10:45:16 +01:00
OlivierDehaene 09b7c26bbd
feat(server): add frequency penalty (#1541) 2024-02-08 18:41:25 +01:00
drbh bd405e035b
Impl simple mamba model (#1480)
This draft PR is a work in progress implementation of the mamba model.
This PR currently loads weights, and produces correct logits after a
single pass.

This PR still needs to correctly integrate this model so it produces
tokens as expected, and apply optimization to avoid all copies during
runtime/unnecessary operations.

#### Helpful resources
[Mamba: Linear-Time Sequence Modeling with Selective State Spaces
(Albert Gu and Tri Dao)](https://arxiv.org/abs/2312.00752)
https://github.com/johnma2006/mamba-minimal

https://github.com/huggingface/candle/blob/main/candle-examples/examples/mamba-minimal/model.rs
https://github.com/huggingface/transformers/pull/28094

Notes: this dev work is currently targeting `state-spaces/mamba-130m`,
so if you want to test please use that model. Additionally when starting
the router the prefill needs to be limited: `cargo run --
--max-batch-prefill-tokens 768 --max-input-length 768`


## Update / Current State

Integration tests have been added and basic functionality such as model
loading is supported.

```bash
cd integration-tests
pytest -vv models/test_fused_kernel_mamba.py
```
- [x] add tests
- [x] load model
- [x] make simple request 
- [ ] resolve warmup issue
- [ ] resolve output issues


fetching models tested during dev
```bash
text-generation-server download-weights state-spaces/mamba-130m
text-generation-server download-weights state-spaces/mamba-1.4b
text-generation-server download-weights state-spaces/mamba-2.8b
```

The server can be run 
```bash
cd server
 MASTER_ADDR=127.0.0.1 MASTER_PORT=5555 python text_generation_server/cli.py serve state-spaces/mamba-2.8b
```

router
```bash
cargo run
```

make a request
```bash
curl -s localhost:3000/generate \
    -X POST \
    -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
    -H 'Content-Type: application/json' | jq
```

response
```json
{
  "generated_text": "\n\nDeep learning is a machine learning technique that uses a deep neural network to learn from data."
}
```

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2024-02-08 10:19:45 +01:00
Dean Wyatte 13c62be467
GPTNeoX: Use static rotary embedding (#1498)
# What does this PR do?

`transformers` 4.35 removed rotary embeddings from GPTNeoX's weights
([link to line
diff](253f9a3f97 (diff-0e2a05d86c82e96f516db8c14070ceb36f53ca44c6bc21a9cd92ad2e777b9cf1R298))).
This applies the same fix as
https://github.com/huggingface/text-generation-inference/pull/793 which
generates them on-the-fly using the appropriate value from the config
file

Fixes
https://github.com/huggingface/text-generation-inference/issues/1460

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [x] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
[here are tips on formatting
docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

@OlivierDehaene OR @Narsil
2024-02-01 09:34:11 +01:00
Nicolas Patry 069895b985
Fixing top_n_tokens. (#1497)
# What does this PR do?

Superseeds #1459

The fix works as follows.
We updated next_token_chooser to return all logprbs, then
batch_top_n_tokens, now also gets accepted_ids + speculated_length (so
it knows how to interpret the flat logprobs).

We then update the code to return lists ot `Tokens` that it expects.
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2024-01-26 20:13:47 +01:00
OlivierDehaene c2d4a3b5c7
v1.4.0 (#1494) 2024-01-26 19:04:57 +01:00
Nicolas Patry ac49972752
Add sealion mpt support (#1477)
# What does this PR do?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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---------

Co-authored-by: Choon Meng Tan <choonmeng@aisingapore.org>
Co-authored-by: David Ong Tat-Wee <13075447+ongtw@users.noreply.github.com>
2024-01-26 14:05:02 +01:00
drbh 7e2a7433d3
feat: adds phi model (#1442)
This PR adds basic modeling for phi-2 

run
```bash
text-generation-server \
    serve \
    microsoft/phi-2 \
    --revision 834565c23f9b28b96ccbeabe614dd906b6db551a
```


test
```bash
curl -s localhost:3000/generate \
   -X POST \
   -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
   -H 'Content-Type: application/json' | jq .
# {
#   "generated_text": "\nDeep learning is a subset of machine learning that uses artificial neural networks to learn from data. These"
# }
```



notes 
- recently (~1 day ago) the Phi weights and model were updated to
accommodate adding [GQA/MQA attention to the
model.](https://github.com/huggingface/transformers/pull/28163) This
impl expects the original model format so a fixed revision is required
at the moment.
- this PR only includes a basic implementation of the model and can
later be extended for support Flash and Sharded versions as well as make
use of better optimization
2024-01-25 15:37:53 +01:00
PYNing da27fbdfdb
Fix local load for Medusa (#1420)
# What does this PR do?

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Close #1418 
Close #1415

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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Here are the
[documentation
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- [ ] Did you write any new necessary tests?


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2024-01-10 18:36:20 +01:00
OlivierDehaene 564199bab3
feat: update exllamav2 kernels (#1370)
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-12-21 17:25:22 +01:00
OlivierDehaene 1b1bfa49b0
fix: fix logic if sliding window key is not present in config (#1352) 2023-12-15 14:56:17 +01:00
OlivierDehaene 9b56d3fbf5
feat: relax mistral requirements (#1351)
Close #1253 
Close #1279
2023-12-15 12:52:24 +01:00
OlivierDehaene 37555cf4e8
fix: max_past default value must be -1, not 0 (#1348) 2023-12-15 01:18:39 +01:00
OlivierDehaene 50b495f3d8
feat: add more latency metrics in forward (#1346) 2023-12-14 15:59:38 +01:00
OlivierDehaene 44b267ab22 fix: fix gpt-q params loading 2023-12-14 11:02:16 +01:00
OlivierDehaene 82670d9786
feat: add quant to mixtral (#1337) 2023-12-12 17:55:03 +01:00
OlivierDehaene ec6d4592d5 v1.3.1 2023-12-11 16:46:44 +01:00
OlivierDehaene 72ee382ded chore: formatting 2023-12-11 14:49:52 +01:00
OlivierDehaene 3a521c92b3
feat: mixtral (#1328) 2023-12-11 14:43:40 +01:00
Nicolas Patry 9ecfa16b12
Speculative (#1308) 2023-12-11 12:46:30 +01:00
Nicolas Patry ba552e1a82
Let each model resolve their own default dtype. (#1287)
# What does this PR do?

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2023-11-28 17:54:26 +01:00
fxmarty b2b5df0e94
Add RoCm support (#1243)
This PR adds support for AMD Instinct MI210 & MI250 GPUs, with paged
attention and FAv2 support.

Remaining items to discuss, on top of possible others:
* Should we have a
`ghcr.io/huggingface/text-generation-inference:1.1.0+rocm` hosted image,
or is it too early?
* Should we set up a CI on MI210/MI250? I don't have access to the
runners of TGI though.
* Are we comfortable with those changes being directly in TGI, or do we
need a fork?

---------

Co-authored-by: Felix Marty <felix@hf.co>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: Your Name <you@example.com>
2023-11-27 14:08:12 +01:00
Vince Jankovics c6bb76703f
Fix IDEFICS dtype (#1214)
# What does this PR do?

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This forces the use of `bfloat16` for IDEFICS. The issue is that with
`float16` the 80b model gives garbage output. Let me know if this
solution is not appropriate and I'll adjust accordingly. For the details
see below.

The current behaviour:
```sh
$ curl 127.0.0.1:8080/generate -X POST -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' -H 'Content-Type: application/json'
{"generated_text":""}
```

On closer inspection with:
```python
import requests

headers = { "Content-Type": "application/json"}

query = "What is Deep Learning?"
data = {
    "inputs": query,
    "parameters": {
        "max_new_tokens": 10,
        "return_full_text": True,
        "decoder_input_details": True,
        "do_sample": False,
    },
}

api_url = "http://127.0.0.1:8080"
response = requests.post(api_url + "/generate", headers=headers, json=data).json()

for i in ['prefill', 'tokens']:
    print(f'### {i}')
    print(repr(''.join([t['text'] for t in response['details'][i]])))
```

Prints:
```
### prefill
'<s>WhatisDeepLearning?'
### tokens
'<unk><unk><unk><unk><unk><unk><unk><unk><unk><unk>'
########
```

With the change in this PR it prints:
```
### prefill
'<s>WhatisDeepLearning?'
### tokens
'\n\nDeep Learning is a subset of machine'
```

Note, using the Transformers implementation (with
`IdeficsForVisionText2Text.from_pretrained`) produces the latter
(correct) output as well.
This only happens with the 80b model, the 9b model is not as sensitive
to the dtype (as also mentioned in the code).

The reason for "forcing" this in the IDEFICS init method, is because if
quantization is used, then the dtype cannot be set explicitly. And since
it's left as `None`, it's set to `float16` by default
[here](96a982ad8f/server/text_generation_server/models/__init__.py (L90)).
I.e. there's no other way to manually change the dtype if someone is
using quantization:
```sh
$ docker run .... ghcr.io/huggingface/text-generation-inference:latest --model-id HuggingFaceM4/idefics-80b-instruct --dtype bfloat16 --quantize bitsandbytes-nf4
.....
2023-10-31T12:42:26.710401Z  INFO shard-manager: text_generation_launcher: Starting shard rank=0
2023-10-31T12:42:30.315734Z ERROR shard-manager: text_generation_launcher: Shard complete standard error output:

Traceback (most recent call last):

  File "/opt/conda/bin/text-generation-server", line 8, in <module>
    sys.exit(app())

  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/cli.py", line 80, in serve
    raise RuntimeError(

RuntimeError: Only 1 can be set between `dtype` and `quantize`, as they both decide how goes the final model.
 rank=0
Error: ShardCannotStart
2023-10-31T12:42:30.414010Z ERROR text_generation_launcher: Shard 0 failed to start
2023-10-31T12:42:30.414044Z  INFO text_generation_launcher: Shutting down shards
```

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-11-23 15:00:09 +01:00
OlivierDehaene 96a982ad8f fix: better warmup error 2023-10-25 10:18:58 +02:00
OlivierDehaene 12590fdcce
feat: paged attention v2 (#1183) 2023-10-23 12:29:25 +02:00
Mario928 9179605e1e
Fix: Replace view() with reshape() in neox_modeling.py to resolve RuntimeError (#1155) 2023-10-19 11:54:26 +02:00
momonga 7402a355dc
Fix calling cuda() on load_in_8bit (#1153)
This PR addresses an issue where calling `model = model.cuda()` would
throw a ValueError when `quantize` is set to "bitsandbytes".

```
> File "/opt/conda/lib/python3.9/site-packages/text_generation_server/server.py", line 147, in serve_inner
    model = get_model(
  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/models/__init__.py", line 295, in get_model
    return CausalLM(
  File "/opt/conda/lib/python3.9/site-packages/text_generation_server/models/causal_lm.py", line 515, in __init__
    model = model.cuda()
  File "/opt/conda/lib/python3.9/site-packages/transformers/modeling_utils.py", line 1998, in cuda
    raise ValueError(
ValueError: Calling `cuda()` is not supported for `4-bit` or `8-bit` quantized models. Please use the model as it is, since the model has already been set to the correct devices and casted to the correct `dtype`.
```

Co-authored-by: mmnga <mmnga1mmnga@gmail.com>
2023-10-19 10:42:03 +02:00
Nicolas Patry e9cdf6225f
Hotfixing idefics base64 parsing. (#1103)
# What does this PR do?

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2023-10-05 13:35:26 +02:00
Nicolas Patry 66ce2fa7c1
Receive base64 encoded images for idefics. (#1096)
# What does this PR do?

Fix #1095

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2023-10-04 17:35:29 +02:00
Nicolas Patry 1bebb9e76b
Update idefics_image_processing.py (#1091)
# What does this PR do?

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2023-10-03 12:25:06 +02:00
Nicolas Patry 85acb11ba0
Handling bloom prefix. (#1090)
# What does this PR do?

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2023-10-03 11:55:10 +02:00
Leo Tronchon b8fefa6b55
raise exception on invalid images (#999)
# What does this PR do?
This PR is meant to handle cases in which the images provided are
invalid.

## Who can review?

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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-10-03 10:26:10 +02:00
Nicolas Patry 5ba53d44a1
Fixing eetq dockerfile. (#1081)
# What does this PR do?

Fixes #1079 
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2023-09-29 11:19:06 +02:00
OlivierDehaene 3b56d7669b
feat: add mistral model (#1071) 2023-09-28 09:55:47 +02:00
zhangsibo1129 1e3ec3c91f
Complete FastLinear.load parameters in OPTDecoder initialization (#1060)
# What does this PR do?

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`FastLinear.load` requires 4 parameters, but in the following only 3 are
given. This PR fix this.

```python
# server/text_generation_server/models/custom_modeling/opt_modeling.py
        if config.word_embed_proj_dim != config.hidden_size:
            self.project_out = FastLinear.load(
                config, prefix="model.decoder.project_out", bias=False
            )
        else:
            self.project_out = None

        if config.word_embed_proj_dim != config.hidden_size:
            self.project_in = FastLinear.load(
                config, prefix="model.decoder.project_in", bias=False
```

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2023-09-27 12:25:59 +02:00
OlivierDehaene 47954b81e9
feat: format code (#1070) 2023-09-27 12:22:09 +02:00
Nicolas Patry b32e9ce9d5
Remove the stripping of the prefix space (and any other mangling that tokenizers might do). (#1065)
Superseed #1024


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---------

Co-authored-by: bangoz <ch_xie@pku.edu.cn>
2023-09-27 12:13:45 +02:00
Vincent Brouwers 8672cad2cb
Fix top_n_tokens returning non-log probs for some models (#1023)
# What does this PR do?

I made an embarrassing mistake where I accidentally passed normal
softmax probabilities into `batch_top_tokens` for `CausalLM` and
`Seq2SeqLM`.

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2023-09-26 16:16:43 +02:00
Victor SANH 1fff6746ab
Fix position ids logic instantiation of idefics vision part (#1064)
Problem and fix is described here:
https://huggingface.co/HuggingFaceM4/idefics-9b/discussions/9

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-09-26 15:41:15 +02:00
Nicolas Patry 2f51645ad7
Fix GQA llama + AWQ (#1061)
# What does this PR do?

Fixes #1056

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2023-09-26 08:27:50 +02:00
Nicolas Patry c5de7cd886
Add AWQ quantization inference support (#1019) (#1054)
# Add AWQ quantization inference support

Fixes
https://github.com/huggingface/text-generation-inference/issues/781

This PR (partially) adds support for AWQ quantization for inference.
More information on AWQ [here](https://arxiv.org/abs/2306.00978). In
general, AWQ is faster and more accurate than GPTQ, which is currently
supported by TGI.

This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors
(in `requirements.txt`, just one line change).

Quick way to test this PR would be bring up TGI as follows:

```
text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq

text-generation-launcher \
--huggingface-hub-cache ~/.cache/huggingface/hub/ \
--model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \
--trust-remote-code --port 8080 \
--max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \
--quantize awq
```

Please note:
* This PR was tested with FlashAttention v2 and vLLM.
* This PR adds support for AWQ inference, not quantizing the models.
That needs to be done outside of TGI, instructions

[here](f084f40bd9).
* This PR only adds support for `FlashLlama` models for now.
* Multi-GPU setup has not been tested. 
* No integration tests have been added so far, will add later if
maintainers are interested in this change.
* This PR can be tested on any of the models released

[here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models).

Please refer to the linked issue for benchmarks for

[abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq)
vs

[TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ).

Please note, AWQ has released faster (and in case of Llama, fused)
kernels for 4-bit GEMM, currently at the top of the `main` branch at
https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit
that has been tested to work. We can switch to latest commit later on.

## Who can review?

@OlivierDehaene OR @Narsil

---------



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---------

Co-authored-by: Abhinav M Kulkarni <abhinavkulkarni@gmail.com>
Co-authored-by: Abhinav Kulkarni <abhinav@concentric.ai>
2023-09-25 15:31:27 +02:00
Nicolas Patry fef36cea42
Fixing t5 loading. (#1042)
# What does this PR do?

Fixes #1038

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2023-09-25 12:22:28 +02:00
Vincent Brouwers 123749a3c9
Fix missing arguments in Galactica's from_pb (#1022)
# What does this PR do?

Fixes #1004

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2023-09-21 08:15:59 +02:00
Wang, Yi eeaa22ab04
enable bfloat16 for cpu (#1034)
if there's no cuda. disable custom kernels

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
2023-09-19 17:19:28 +02:00
xiaobin 4cce84301b
fit for baichuan models (#981)
As more and more people begin to use Baichuan's open-source models, the
influence of Baichuan models is growing, especially in China. Many
community members are interested in adding support for Baichuan models
to TGI. Meanwhile, Baichuan is a very open company, and in the future,
it plans to open-source more and more models, taking all this into
consideration, we would like to add support for the Baichuan model to
TGI. To do this, we need to make some changes, which we hope can be
merged into the main branch of TGI. In the future, we would be happy to
help maintain support for Baichuan models in TGI. We sincerely hope that
our pull request can be accepted. Thank you.

By the way, the changes of this time mainly for supporting Baichuan-7B.

---------

Co-authored-by: xiaoyuze <xiaoyuze@baichuan.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-09-08 16:51:34 +02:00
Victor SANH 2bc287bfcd
small fix on idefics (#954)
transposing the fixes from
https://github.com/huggingface/transformers/pull/25787
2023-09-01 18:44:34 +02:00
Vincent Brouwers 8a5f564942
Fix Falcon weight mapping for H2O.ai checkpoints (#953)
# What does this PR do?
During the safetensor conversion, duplicate weights are removed.
However, which of the duplicates gets removed, differs per checkpoint.
In some, like `h2oai/h2ogpt-oig-oasst1-falcon-40b`, the weight
`transformer.word_embeddings.weightSafetensor` gets removed. In others,
`lm_head.weight` gets removed. Long story long, we need to support both.

Originally, f018143 mapped `lm_head` to `word_embeddings`. Then ac736fd
switched this around. This commit merges them and allows for both.

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@Narsil, you wrote both commits I referenced in this PR. I think you'll
understand this change :)
2023-08-31 21:15:14 +02:00
Nicolas Patry 7c2e0af2a6
Fix f180 (#951)
# What does this PR do?

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2023-08-30 11:09:46 +02:00
Nicolas Patry 211b54ac41
Rebased #617 (#868)
# What does this PR do?

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---------

Co-authored-by: Vincent Brouwers <vincent.brouwers@ing.com>
2023-08-28 11:43:47 +02:00
Nicolas Patry e605c2a43e
Supporting code llama. (#918)
# What does this PR do?

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2023-08-24 18:54:47 +02:00
Nicolas Patry bce5e22444
Adding Idefics multi modal model. (#842)
Co-Authored-By: Victor Sanh <victorsanh@gmail.com>


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---------

Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 14:38:49 +02:00
Nicolas Patry 2e68ac01c0
"Fix" for rw-1b. (#860)
# What does this PR do?

- New "falcon" layout on this repo
- No alibi
- `transformers` already modifying cache layout in our stead (same
  modifications).
- Output is garbage. Not sure why.

Does not fix #826 but it's a step.

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2023-08-17 09:05:41 +02:00
Dong Shin a072660bf5
fix: LlamaTokenizerFast to AutoTokenizer at flash_llama.py (#619)
# What does this PR do?

A few tokenizer_config in huggingface use LlamaTokenizer, so I think I
would have selected `LlamaTokenizer` before.

For a few cases where you're using a llama structure but not a llama
tokenizer, why not make it to call the AutoTokenizer in exception
handling.

In the case of `decapoda-research/llama-7b-hf`, LLamaTokenizer is still
being used in config.json, so it should be called through`
LlamaTokenizer`.
Also, if an exception is thrown by LlamaTokenizer, it will cause
`LlamaTokenzierFast` to be called from AutoTokenizer.


Fixes # 560


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@Narsil
2023-08-14 14:20:18 +02:00
Nicolas Patry 0e8b47811e
Llama change. (#793)
# What does this PR do?

Reflecting
https://github.com/huggingface/transformers/pull/24998

Current status wants to make sure integration tests *are* broken with
this.


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2023-08-08 13:43:40 +02:00
Nicolas Patry c4dac9f3dc
Update __init__.py (#794)
# What does this PR do?

Fixes #787
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2023-08-08 12:09:51 +02:00
Nicolas Patry 16fadcec57
Merge BNB 4bit. (#770)
# What does this PR do?


See #626 
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---------

Co-authored-by: krzim <zimmerk4@live.com>
2023-08-03 23:00:59 +02:00
Nicolas Patry ac736fd89c
feat(server): Add native support for PEFT Lora models (#762)
- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
  chosen model id**

PROs:

- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE

CONs:

- Creates a local merged model in unusual location, potentially
  not saved across docker reloads, or ovewriting some files if the PEFT
  itself was local and containing other files in addition to the lora

Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
  code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
  location for this new model), but it would
  introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
  `download-weights` and asking user to restart with the actual local
  model location


Fix #482 


# What does this PR do?

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2023-08-03 17:22:45 +02:00
zspo bd3088748e
add FastLinear import (#750)
# What does this PR do?

Fixes #749 

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Co-authored-by: p_spozzhang <p_spozzhang@tencent.com>
2023-08-02 20:04:46 +02:00
Ikko Eltociear Ashimine 2a13f1a046
chore: fix typo in mpt_modeling.py (#737)
# What does this PR do?
Fixed typo.
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implemetation -> implementation


## Before submitting
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2023-07-31 15:43:44 +02:00
Nicolas Patry 932bdd93ff
Adding Rope scaling. (#741)
# What does this PR do?


- Adds Rope NTK scaling.

Done because
https://github.com/huggingface/text-generation-inference/pull/529 was
closed
Took some code from
https://github.com/huggingface/transformers/pull/24653

- `--rope-scaling` and `--rope-factor` are added separately. I
considered having a single one and parsing something line ("linear:4.0"
, or "dynamic") but decided against
it because it would push more parsing+validation a bit everywhere (both
in the launcher and the server).


Fixes #512




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2023-07-31 15:38:47 +02:00
Jae-Won Chung b9633c46d0
Fix typing in `Model.generate_token` (#733)
## What does this PR do?

This PR fixes a minor type annotation issue in the signature of
`Model.generate_token`.

All existing overrides of `Model.generate_token` return
`Tuple[List[Generation], Optional[B]]`:

3ef5ffbc64/server/text_generation_server/models/causal_lm.py (L535-L537)

3ef5ffbc64/server/text_generation_server/models/flash_causal_lm.py (L802-L804)

3ef5ffbc64/server/text_generation_server/models/seq2seq_lm.py (L589-L591)

I suspect that back in 017a2a8c when `GeneratedText` and `Generation`
were separated, the function signature was not updated.

## Before submitting
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other checks if that's the case).
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CC @OlivierDehaene
2023-07-31 14:35:14 +02:00
OlivierDehaene ab96b9aec3
feat(server): support new falcon config (#712) 2023-07-27 18:38:57 +02:00
OlivierDehaene 8bd0adb135
fix(server): fix quantization python requirements (#708) 2023-07-27 12:28:10 +02:00
Nicolas Patry a0d55358d2
feat(server): Using `quantize_config.json` instead of GPTQ_BITS env variables. (#671)
- Current PR is not great because we're side stepping the
  `Weights.__init__` but Weights shouldn't requires anything related
  to the config or the model_id as it aims to be a simple Wrapper
  over multi file loading.
- Ideal solution would be to use something like Rust enum
  ```
  enum Quantize{
    Bitandbytes(Bitsandbytes),
    GPTQ(bits: usize, groupsize: usize)
  ```
  And passing that around during load. Unfortunately we don't
  have access to this, so for now, side-stepping seems easier.

- Re-enabling groupsize<0 with exllama (confirmed it works.)

Helps #601 

In next steps we should make sure our quantization script uses that
format and make it standard.


# What does this PR do?

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2023-07-25 13:00:27 +02:00
OlivierDehaene 73a4d65d26
feat: add cuda memory fraction (#659)
Close #673
2023-07-24 11:43:58 +02:00
Yang, Bo 15b3e9ffb0
Directly load GPTBigCode to specified device (#618)
This PR directly load GPTBigCode to specified device, avoiding moving
model between devices.

# What does this PR do?
This PR directly load GPTBigCode to specified device, avoiding moving
model between devices.


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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      Pull Request section?
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2023-07-21 11:27:31 +02:00
Nicolas Patry d5b5bc750f
feat(server): Add exllama GPTQ CUDA kernel support #553 (#666)
Just trying to get the integration tests to pass.


# What does this PR do?

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---------

Co-authored-by: Felix Marty <9808326+fxmarty@users.noreply.github.com>
2023-07-21 10:59:00 +02:00
OlivierDehaene bf94df3c71
fix(server): use mem_get_info to get kv cache size (#664)
Close
https://github.com/huggingface/text-generation-inference/issues/649
Close
https://github.com/huggingface/text-generation-inference/issues/651
Close
https://github.com/huggingface/text-generation-inference/issues/653
Close #636
2023-07-20 17:23:49 +02:00
fxmarty 362883f259
fix(server): llama v2 GPTQ (#648)
As per title & reported
https://github.com/huggingface/text-generation-inference/issues/601#issuecomment-1641435956
https://huggingface.co/TheBloke/Llama-2-70B-chat-GPTQ/discussions/5

Test it:

```
GPTQ_BITS=4 GPTQ_GROUPSIZE=1 text-generation-launcher --model-id TheBloke/Llama-2-70B-chat-GPTQ --port 8080 --num-shard 4 --quantize gptq
```
&
```
curl 127.0.0.1:8080/generate \
    -X POST \
    -d '{"inputs":"hey llama","parameters":{"max_new_tokens":256}}' \
    -H 'Content-Type: application/json'
```
2023-07-20 15:02:54 +02:00
OlivierDehaene fe80f5360c
feat(server): auto max_batch_total_tokens for flash att models (#630) 2023-07-19 09:31:25 +02:00
OlivierDehaene 5e6ddfd6a4
fix(server): fix llamav2 config (#635) 2023-07-18 18:49:42 +02:00
Nicolas Patry 211b211ec0
feat(server): add support for llamav2 (#633) 2023-07-18 18:09:53 +02:00
OlivierDehaene 3b71c38558
feat(server): flash attention v2 (#624) 2023-07-18 16:21:18 +02:00
OlivierDehaene a2cf1bdb2f fix(server): empty_cache when stopped 2023-07-15 13:58:19 +02:00
OlivierDehaene f2f0289fb9 feat(server): empty cache on errors 2023-07-12 17:06:19 +02:00
Adam Kowalski 7f9072228a
fix(server): Adding logger import to t5_modeling.py (#585)
Logger is referenced during the apex importing but is not imported,
causing a NameError
2023-07-12 10:40:32 +02:00
Nicolas Patry db4efbf4bc
fix(server): T5 weights names. (#582)
Fixes #541
2023-07-12 10:01:42 +02:00
Nicolas Patry 5bd2ab6583
feat(server): Support for env value for GPTQ_BITS and GPTQ_GROUPSIZE. (#580)
# What does this PR do?

Some models are already converted, and do not have those values in the
file, this enables users to use them with less friction.

Went for pure env based because adding flags would end up (imo) very
tedious to maintain. There's a lot of sanitation to do: those flags
would be errors if not used in conjuction with `--quantize gptq`.
Then the flags need to exist in the launcher and the server passing them
all throughout all function calls.

This PR is intended as an easy escape hatch, not the defacto method to
use gptq in TGI.

Fixes #500
2023-07-12 10:00:02 +02:00
Nicolas Patry f0181436f4
fix(server): Fixing RW code (it's remote code so the Arch checking doesn't work to see which weights to keep). (#579)
Fixes #555
2023-07-12 09:51:34 +02:00
OlivierDehaene b4024edd45
feat: better errors for warmup and TP (#575)
Close #571
2023-07-10 14:47:15 +02:00
OlivierDehaene c4bb5264ac
fix(server): decrease memory fragmentation (#557) 2023-07-06 14:28:33 +02:00
OlivierDehaene 31e2253ae7
feat(server): use latest flash attention commit (#543)
@njhill FYI
2023-07-04 20:23:55 +02:00
Antoni Baum 2a101207d4
fix(server): Handle loading from local files for MPT (#534)
This PR allows the MPT model to be loaded from local files. Without this
change, an exception will be thrown by `hf_hub_download` function if
`model_id` is a local path.
2023-07-04 18:37:25 +02:00
Nicolas Patry 1da07e85aa
feat(server): Add Non flash MPT. (#514)
# What does this PR do?


This adds a non flash version of MPT.
Flash is harder because we need to create a bias ready cuda kernel of
flash attention.

Fixes
https://github.com/huggingface/text-generation-inference/issues/361
Fixes
https://github.com/huggingface/text-generation-inference/issues/491
Fixes
https://github.com/huggingface/text-generation-inference/issues/290
2023-07-03 13:01:46 +02:00
Nicolas Patry ecf6dc3a5a
feat: Add the option to force another dtype than `f16`. (#513) 2023-06-30 20:30:09 +02:00
OlivierDehaene e74bd41e0f
feat(server): add paged attention to flash models (#516)
Closes #478
2023-06-30 19:09:59 +02:00
Nicolas Patry aefde28b45
feat(server): Add inference support for GPTQ (llama + falcon tested) + Quantization script (#438)
Let's start discussing implementation.

- Need to expose the quantization scripts (either included here or add
doc on how to use https://github.com/qwopqwop200/GPTQ-for-LLaMa)
- Make sure GPTQ works for multiple models (priority to Falcon).

Currently it means that every place we use `get_{tensor|sharded}` to
check for quantization.

My idea is to reintegrate as much as possible into `utils/layer.py` by
expanding `load_multi` to be a bit more generic.
This might require some thinking, but ultimately the
`qweight,qzeros,scales,g_idx` should be in a single place, and
independant of bias presence.

# What does this PR do?

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other checks if that's the case).
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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the
[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes?
Here are the
[documentation
guidelines](https://github.com/huggingface/transformers/tree/main/docs),
and
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- [ ] Did you write any new necessary tests?


## Who can review?

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---------

Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-06-26 12:27:01 +02:00
Nicolas Patry 49b4b33e80
feat(server): Update convert logic. (#483)
Should be more robust to shared tensors (ok when using
      `from_pretrained). But forcing us to add new checks in our loading
      code (since the chosen key to keep might be different from
      `transformers`).

---------

Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal>
2023-06-23 12:40:46 +02:00
Nicolas Patry c9c65ab323
fix(server): Fixing T5 in case the names are mixed up. (#475) 2023-06-20 18:03:36 +02:00
OlivierDehaene 53aa9194c8
fix(server): fix warpers on CPU (#472)
Closes #471
2023-06-20 11:06:10 +02:00
OlivierDehaene ece7ffa40a
feat(server): improve flash attention import errors (#465)
@lewtun, is this enough?

Closes #458
Closes #456
2023-06-19 09:53:45 +02:00
OlivierDehaene f59fb8b630
feat(router): add ngrok integration (#453) 2023-06-16 16:25:11 +02:00
OlivierDehaene 5ce89059f8
feat(server): pre-allocate past key values for flash causal LM (#412) 2023-06-12 18:30:29 +02:00
OlivierDehaene e496c9ba5b
feat(server): optimize dist ops (#434) 2023-06-09 11:55:29 +02:00
Nicolas Patry abd58ff82c
feat(server): Rework model loading (#344)
# What does this PR do?

Reworked the loading logic. Idea is to use cleaner loading code:

- Remove need for `no_init_weights`
- Remove all weird `bnb_linear` and `load_weights` and
`post_load_weights`.

New code layout:

- New class `Weights` in charge of handling loading the weights from
multiple files into appropiate tensors (potentially sharded)
- TP layers now are "shells", they contain the code to know what kind of
sharding we need + eventual `all_reduce`. They do not inherit from
linear, but they contain some kind of Linear instead
- the contained linear can be either FastLinear, BnbLinear or GPTq
Linear next.
- All modeling code is explictly made for sharding, process group is
just no-ops for non sharded code (removes a lot of test cases)

![Screenshot from 2023-05-19
23-19-59](https://github.com/huggingface/text-generation-inference/assets/204321/9a802654-74a3-488c-87a8-073743a6143f)

---------

Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.taildb5d.ts.net>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
2023-06-08 14:51:52 +02:00
OlivierDehaene 6abec14a7e
feat(server): batch tokenization for flash causal lm (#411) 2023-06-05 16:09:41 +02:00
OlivierDehaene 895c5f1562
feat(server): only compute prefill logprobs when asked (#406)
Close #288
2023-06-02 17:12:30 +02:00
OlivierDehaene e7248fe90e v0.8.2 2023-06-01 19:49:13 +02:00
OlivierDehaene 95d3546976
feat(server): load santacoder/starcoder models with safetensors (#393)
Fix #366
2023-06-01 12:10:35 +02:00
OlivierDehaene c0928e6f26
feat(server): remove trust_remote_code requirement for falcon models (#396) 2023-06-01 12:07:41 +02:00
OlivierDehaene d69a0633be
fix(server): fix has_position_ids (#395)
Fix #389
2023-06-01 11:41:35 +02:00
OlivierDehaene 337afb2842
fix(server): fix bnb quantization for CausalLM models (#385) 2023-05-31 11:48:28 +02:00
OlivierDehaene 87dc034b59
feat(server): add retry on download (#384) 2023-05-31 10:57:53 +02:00
OlivierDehaene b8b950b37c
feat(server): support RefinedWeb models (#379) 2023-05-30 18:25:19 +02:00
OlivierDehaene bf7f1d5434 fix(server): fix quantization 2023-05-30 13:56:03 +02:00
CL-Shang 5fde8d9991
Fix issue when load AutoModelForSeq2SeqLM model (#370) 2023-05-26 12:31:47 +02:00
OlivierDehaene 62f91f78ac
feat(server): support vectorized warpers in flash causal lm (#317)
Co-authored-by: Joel Lamy-Poirier <joel.lamy-poirier@servicenow.com>
2023-05-26 12:30:27 +02:00
OlivierDehaene 218c9adaa5
feat: decrease IPC proto size (#367)
Closes #307 #308
2023-05-24 19:19:57 +02:00
OlivierDehaene e3e487dc71
feat(server): support trust_remote_code (#363) 2023-05-23 20:40:39 +02:00
OlivierDehaene e9669a4085
feat(server): do not use device_map auto on single GPU (#362) 2023-05-23 19:12:12 +02:00
OlivierDehaene cfaa858070
feat(server): support fp16 for t5 (#360)
Fixes #349
2023-05-23 18:16:48 +02:00
OlivierDehaene 4f4c9c1665
fix(server): t5 cannot run in f16 (#356)
Fix #349
2023-05-23 12:15:54 +02:00
OlivierDehaene 91d9beec90
fix(server): fix init for flash causal lm (#352)
Fixes #347
2023-05-22 15:05:32 +02:00
OlivierDehaene e649bf9a55
feat(server): Support BLOOMChat-176B (#348) (#351)
@njhill, 
temporary workaround to be able to run our CI as secrets are not
available to runners run by external contributors. I will ask around to
see if there is a better way.

Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-05-22 13:36:00 +02:00
OlivierDehaene 5a58226130
fix(server): fix decode token (#334)
Fixes #333

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-05-16 23:23:27 +02:00
OlivierDehaene e71471bec9
feat: add snapshot testing (#282) 2023-05-15 23:36:30 +02:00
Nicolas Patry f58f0a0364
Single place for TP layers + Dropout Layer Norm + FastLinear (#329)
# What does this PR do?

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2023-05-15 17:30:47 +02:00
Nicolas Patry d7a97aa0b6
Removing dead variables. (#327)
# What does this PR do?

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- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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2023-05-15 15:14:17 +02:00
Nicolas Patry 91e674bb85
Lifting check_unitialized. (#325)
# What does this PR do?

Lifting check_unitialized.

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      Pull Request section?
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[forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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2023-05-15 11:32:25 +02:00
Nicolas Patry 73d84c6ee5
Hotfixes for santacoder/bigcode. (#294)
# What does this PR do?

Hotfixes:

- Uses `model_type`=`gpt_bigcode` for more general usage.
- Hotfixes linked lm_head vs wte_embedding (safetensors file do not
contain the key, correctly when the file is sharded, where as pytorch
copies the tensor)


<!--
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## Before submitting
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      Pull Request section?
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      to it if that's the case.
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Here are the
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---------

Co-authored-by: Ubuntu <ubuntu@ip-172-31-41-161.ec2.internal>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
2023-05-15 10:35:20 +02:00
OlivierDehaene 8a8f43410d
chore(docker): use nvidia base image (#318) 2023-05-12 17:32:40 +02:00
Nicolas Patry 76a48cd365
feat(server): GPTQ quantization (step1) (#277)
Changes only the type from `bool` to `Option<Enum>` pretty much
everywhere.
- Use `Optional[str]` in Python (easier to manage than importing type
everywhere). Except for the cli to get proper validation
- Updated all models to handle gracefully new values. (Error out if
unknown value, or gptq since not implemented).

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
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      Pull Request section?
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      to it if that's the case.
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2023-05-12 14:46:41 +02:00
OlivierDehaene 745f596c88
feat(server): use float16 (#304) 2023-05-10 15:51:10 +02:00
OlivierDehaene 68e9d6ab33
feat(server): shard token decode (#303) 2023-05-10 15:48:21 +02:00
OlivierDehaene ad66f6ef9a
feat(server): optim flash causal lm decode_token (#285) 2023-05-09 18:26:19 +02:00
OlivierDehaene 85aa7e2e7b
feat(server): support hf endpoint weight layout (#266) 2023-05-03 11:36:24 +02:00
OlivierDehaene 4096000e34
fix(server): fix typo in tokenizers decode (#269)
closes #268
2023-05-03 10:10:34 +02:00
Ehsan M. Kermani f092ba9b22
feat(server): add watermarking tests (#248) 2023-04-27 19:16:35 +02:00
Nick Hill 34bca0b8d3
fix(server): Small tidy of code from recent changes (#251)
remaining_decode_tokens was calculated twice in Seq2SeqLMBatch.filter()
2023-04-27 09:57:28 +02:00
Nick Hill b4cf832c40
fix(server): fix reshaping of bloom past_key_values in concatenate() (#252)
Introduced in #214 

Fixes #249
2023-04-27 09:51:27 +02:00
OlivierDehaene ebc74d5666
feat(router): use number of tokens in batch as input for dynamic batching (#226)
Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-04-24 17:59:00 +02:00
Nick Hill 4a7dd4085a
feat(server): reduce memory requirement (#214) 2023-04-24 14:15:42 +02:00
OlivierDehaene 4b460e72fb
fix(server): fix flash batch filtering (#220) 2023-04-21 20:26:01 +02:00
OlivierDehaene 1ffea36ec2
fix(server): fix flash causal (#219) 2023-04-21 19:49:08 +02:00
OlivierDehaene 86bca365df
fix(server): fix flash causal (#218) 2023-04-21 19:42:16 +02:00
OlivierDehaene afc5b999d0
fix(server): cleanup new flash past_key_values logic (#217) 2023-04-21 16:19:04 +02:00
OlivierDehaene db4cb5e4ed
fix(server): fix past key values logic (#216)
@njhill fyi
2023-04-21 15:59:18 +02:00
OlivierDehaene 343437c7b5
feat(router): add device and dtype info (#215) 2023-04-21 15:36:29 +02:00
Nick Hill ac8c0f6fe4
feat(server): flash attention past key value optimizations (#213) 2023-04-21 14:57:18 +02:00
OlivierDehaene 709d8936f6
feat(router): drop requests when client closes the channel (#202) 2023-04-20 11:07:40 +02:00
OlivierDehaene b6ee0ec7b0
feat(router): add git sha to info route (#208) 2023-04-19 21:36:59 +02:00
OlivierDehaene a88c54bb4c
feat(server): check cuda capability when importing flash models (#201)
close #198
2023-04-19 12:52:37 +02:00
OlivierDehaene e14ae3b5e9
feat(server): support quantization for flash models (#200)
closes #197
2023-04-19 12:51:11 +02:00
OlivierDehaene 7a1ba58557
fix(docker): fix docker image dependencies (#187) 2023-04-17 00:26:47 +02:00
OlivierDehaene 880a76eed5
feat(server): support sharded santacoder (#167) 2023-04-12 17:18:08 +02:00
OlivierDehaene 5fa8ae041c
feat(server): optimize decode for sane tokenizers (#170) 2023-04-12 12:03:10 +02:00
OlivierDehaene f26dfd0dc1
feat(server): support OPT models (#55)
OPT models do not all have a `tokenizer.json` file on the hub at the
moment. Can't merge for now.
2023-04-11 19:16:41 +02:00
OlivierDehaene 299217c95c
feat(server): add flash attention llama (#144) 2023-04-11 16:38:22 +02:00
OlivierDehaene 9987960062
feat(router): make router input validation optional (#164) 2023-04-09 20:22:27 +02:00
OlivierDehaene 3f2542bb6a
fix(server): fix escape characters in stop sequence (#155) 2023-04-05 19:37:41 +02:00
OlivierDehaene c0aeb32583
feat(server): flash santacoder (#153) 2023-04-03 19:06:42 +02:00
OlivierDehaene 08b7e4a282
fix(server): fix flash neox rotary embeddings (#150) 2023-03-30 16:12:23 +02:00
OlivierDehaene c9bdaa8b73
feat(server): reduce mlp and attn in one op for flash neox (#145) 2023-03-28 16:51:41 +02:00
Nick Hill 462530c2b0
fix(server): Avoid using try/except to determine kind of AutoModel (#142) 2023-03-27 09:23:22 +02:00
OlivierDehaene 678b2f3900
feat(server): cleanup flash neox loading (#139) 2023-03-26 16:37:21 +02:00
OlivierDehaene d6a93fe992
fix(server): fix flash-neox scores warping (#137) 2023-03-24 18:21:41 +01:00
OlivierDehaene 05e9a796cc
feat(server): flash neoX (#133) 2023-03-24 14:02:14 +01:00