Commit Graph

460 Commits

Author SHA1 Message Date
drbh 762dbf3f19
fix: handle batches with and without grammars (#1676)
This PR correctly handles batches with a mixture of constrained and non
constrained generations.

Currently if batch contains mixed generations the generation will throw
an error because it will incorrectly attempt to constrain a request with
an empty grammar.

We now handled `None` grammars and only apply the mask if needed

Fixes:
https://github.com/huggingface/text-generation-inference/issues/1643
2024-03-28 12:02:01 -04:00
OlivierDehaene 6c4496a1a3
v1.4.4 (#1668) 2024-03-22 18:44:05 +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 de6cb15fa5
fix: improve tool type, bump pydantic and outlines (#1650)
This PR resolves a couple 

- [X] adjusts the tool response to align with openai's tools response
type
- [X] bumps pydantic to `2.6.4` in all apps (resolves dependency issue
when running tests)
- [X] bump `outlines` version and fix import for new name
2024-03-21 12:45:56 -04:00
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
abhishek thakur 0d9917f744
Update peft + transformers + accelerate + bnb + safetensors (#1646) 2024-03-15 13:23:26 +01:00
drbh 7dbaf9e901
fix: correctly index into mask when applying grammar (#1618)
This PR fixes how the grammar mask is index when generating text and
adds a new test to ensure the grammars work with non flash models
2024-03-01 18:22:01 +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)
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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 e6bb3ff81f
v1.4.3 (#1609) 2024-02-28 16:12:14 +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)
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2024-02-26 19:49:28 +01:00
OlivierDehaene 9c1cb81cd8
v1.4.2 (#1585) 2024-02-21 14:50:57 +01:00
OlivierDehaene c86f58d37c
feat: add support for Gemma (#1583) 2024-02-21 14:15:22 +01:00
OlivierDehaene fa8a8e05af
fix(router): fix openapi and add jsonschema validation (#1578) 2024-02-21 11:05:32 +01:00
Nicolas Patry d19c768cb8
Fix mistral with length > window_size for long prefills (rotary doesn't create long enough cos, sin). (#1571)
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2024-02-19 15:23:12 +01:00
OlivierDehaene 4139054b82
v1.4.1 (#1568) 2024-02-16 17:50:57 +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

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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
Jason Stillerman 39af000cb9
Update to peft 0.8.2 (#1537)
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      Pull Request section?
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@OlivierDehaene OR @Narsil
2024-02-08 12:44:04 +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
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2024-02-01 09:34:11 +01:00
dtlzhuangz 0595bf3e9a
feat: eetq gemv optimization when batch_size <= 4 (#1502)
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Add TensorRT-LLM weight-only GEMV kernel support. We extract GEMV kernel
from
[TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM/tree/main/cpp/tensorrt_llm/kernels/weightOnlyBatchedGemv)
to accelerate the decode speed of EETQ when batch_size is smaller or
equal to 4.

- Features

1. There is almost no loss of quantization accuracy.
2. The speed of decoding is 13% - 27% faster than original EETQ which
utilizes GEMM kernel.

- Test
Below is our test on 3090. Environment: torch=2.0.1, cuda=11.8, nvidia
driver: 525.78.01
prompt=1024, max_new_tokens=50

![image](https://github.com/huggingface/text-generation-inference/assets/139844877/98e63b23-23cd-452f-91bd-55ccdc9b7021)


![image](https://github.com/huggingface/text-generation-inference/assets/139844877/5c3132ff-fc1c-4b20-a83f-59b3d5f586b7)



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2024-01-31 12:05:49 +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
fxmarty 650fea1834
GPTQ support on ROCm (#1489)
Tested with
```
CUDA_VISIBLE_DEVICES=0 text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
EXLLAMA_VERSION=1 CUDA_VISIBLE_DEVICES=0 text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
CUDA_VISIBLE_DEVICES="0,1" text-generation-launcher --model-id TheBloke/Llama-2-7B-Chat-GPTQ --quantize gptq
```

all with good and identical results on MI210.

---------

Co-authored-by: Felix Marty <felix@hf.co>
Co-authored-by: OlivierDehaene <olivier@huggingface.co>
Co-authored-by: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com>
2024-01-26 16:27:44 +01:00
Nicolas Patry ac49972752
Add sealion mpt support (#1477)
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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
Nicolas Patry b95732180d
Reinstate exl2 with tp (#1490)
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2024-01-26 14:00:29 +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
Nicolas Patry 7e542d4d05
Fixing non divisible embeddings. (#1476)
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2024-01-24 13:08:41 +01:00
PYNing da27fbdfdb
Fix local load for Medusa (#1420)
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Close #1418 
Close #1415

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2024-01-10 18:36:20 +01:00
R. P. Ruiz 91d7267534
Fix missing make target platform for local install: 'install-flash-attention-v2' (#1414) 2024-01-09 16:19:31 +01:00
OlivierDehaene 564f2a3b75
fix: fix local loading for .bin models (#1419) 2024-01-09 15:21:00 +01:00
OlivierDehaene 630800eed3 v1.3.4 2023-12-22 15:46:04 +01:00
Nicolas Patry 529d7c2591
Fix local load for peft (#1373)
local directory overloaded still needs the directory to locate the
weights files correctly.

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2023-12-21 17:29:23 +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
Nicolas Patry eb8923a97e
Peft safetensors. (#1364)
Works by removing adapter_model.safetensors from being detected as the
core model file (which skips the real peft detection).

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2023-12-20 15:37:14 +01:00
OlivierDehaene d077150eb7
fix: fix gpt-q with groupsize = -1 (#1358) 2023-12-18 16:07:05 +01:00
OlivierDehaene 8428ed1011
fix: fix offline (#1341) (#1347)
@oOraph

---------

Signed-off-by: Raphael Glon <oOraph@users.noreply.github.com>
Co-authored-by: Raphael Glon <oOraph@users.noreply.github.com>
2023-12-18 10:20:08 +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 f3aea78fb6 v1.3.3 2023-12-15 01:20:42 +01:00
OlivierDehaene 37555cf4e8
fix: max_past default value must be -1, not 0 (#1348) 2023-12-15 01:18:39 +01:00
OlivierDehaene 9b78a6eee3 fix: only keep stop sequence buffer if we have some 2023-12-14 17:04:58 +01:00
OlivierDehaene 80a69204c1 fix: slice stopping criteria buffer 2023-12-14 17:01:43 +01:00
OlivierDehaene 083c2de9f8 fix: fix quant linear autotune 2023-12-14 16:45:47 +01:00
OlivierDehaene 773aabdda6 fix: fix triton OutOfResources import 2023-12-14 16:04:26 +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 88aae2595d v1.3.2 2023-12-12 18:10:22 +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 d0841cc8eb v1.3.0 2023-12-11 14:55:03 +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
OlivierDehaene ccd5725a0c v1.2.0 2023-11-30 15:18:15 +01:00
Nicolas Patry ba552e1a82
Let each model resolve their own default dtype. (#1287)
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2023-11-28 17:54:26 +01:00
Nicolas Patry 3c71c656c7
`make install-flash-attn-v2-cuda` should work like `make install-flash-attn-v2` used to work. (#1294)
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2023-11-28 16:28:40 +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
Nicolas Patry ed2a3f617e
Exllama v2 (#1211)
# What does this PR do?

See #1165

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---------

Co-authored-by: Florian Zimmermeister <flozi00.fz@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-24-153.ec2.internal>
2023-11-25 22:38:38 +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
```

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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-11-23 15:00:09 +01:00
OlivierDehaene 35509ff5de
chore: update to torch 2.1.0 (#1182)
Close #1142
2023-11-23 13:38:50 +01:00
Traun Leyden e12c34bd25
Load PEFT weights from local directory (#1260)
# What does this PR do?

Enables PEFT weights to be loaded from a local directory, as opposed to
a hf hub repository. It is a continuation of the work in PR
https://github.com/huggingface/text-generation-inference/pull/762

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Fixes #1259 


## Before submitting
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other checks if that's the case).
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Pull Request section? **Yes but I don't know how to run the tests for
this repo, and it doesn't look like this code is covered anyway**
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[forum](https://discuss.huggingface.co/)? Please add a link
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test coverage for this python module**


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---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-11-23 12:56:17 +01:00
Diwank Singh Tomer 91111a0dc2
Fix missing `trust_remote_code` flag for AutoTokenizer in utils.peft (#1270)
Peft loading function was missing the
`trust_remote_code=trust_remote_code` argument causing the custom
tokenizer code to be not found.


## Before submitting
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other checks if that's the case).
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      Pull Request section?
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@Narsil
2023-11-23 12:41:05 +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
star 648ea06430
fix: EETQLinear with bias in layers.py (#1176) 2023-10-19 12:15:05 +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 00b8f36fba
Prepare for v1.1.1 (#1100)
# What does this PR do?

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2023-10-05 16:09:49 +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 3c373dcc53
Adding yarn support. (#1099)
# What does this PR do?


Fixes #1017

Not sure if there's a mistake here but 

- NousResearch/Yarn-Llama-2-7b-128k seems to be working fine
- TheBloke/Yarn-Llama-2-13B-128K-GPTQ outputs garbage



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2023-10-05 10:11:50 +02:00
Nicolas Patry 87f43814e3
Fixing GPTQ exllama kernel usage. (#1101)
# What does this PR do?

Fixes #1098 
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2023-10-05 10:11:27 +02:00
Martin Vejvar 0e4ee4f107
fix: type hint typo in tokens.py (#1102)
# What does this PR do?
Fixing a list type hint definition (I believe this was a typo).

Allows backward compatibility with Python 3.8 (relevant for
JetPack-enabled systems).

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2023-10-05 09:33:04 +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.

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@Narsil

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-10-03 10:26:10 +02:00
Peter Lowrance bd998d8797
Fix window_size_left for flash attention v1 (#1089)
This fixes flash attention v1 which was always
NotImplementedError("window_size_left is only available with flash attn
v2").

Currently flash_llama_modeling.py doesn't override the default value of
window_size_left when calling attention(..) (line 282). This means that
window_size_left will always be the default of -1, but flash attention
v1 throws an exception if `window_size_left != 0`.

To fix this, we should be checking `window_size_left != -1` before
throwing the NotImplementedError.


Fixes #1084 


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2023-10-02 20:53:14 +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
Nicolas Patry 95a4bb696a
Support eetq weight only quantization (#1068)
# What does this PR do?

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---------

Co-authored-by: zhaosida <zhaosida@corp.netease.com>
2023-09-27 11:42:57 +02:00
Nicolas Patry a049864270
Preping 1.1.0 (#1066)
# What does this PR do?

Upgrade all relevant versions and dependencies.

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2023-09-27 10:40:18 +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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## Before submitting
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@Narsil
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
zhangsibo1129 eba6ab1c5d
fix discard_names bug in safetensors convertion (#1052)
# What does this PR do?

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Model Class attributes `_tied_weights_keys`, `
_keys_to_ignore_on_load_missing` can only be `None` or a List.
`getattr(class_, "_keys_to_ignore_on_load_missing", [])` will return
`None` if `_keys_to_ignore_on_load_missing` is None, and
`discard_names.extend(None)` will trigger an exception, even though
`_tied_weights_keys` exists.

## Who can review?

@OlivierDehaene  @Narsil

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
2023-09-26 15:05:40 +02:00
zhangsibo1129 edc95a0e7d
support local model config file (#1058)
# What does this PR do?

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Support local config file to avoid unexpected `discard_names`, which
causes #1057.

In the case of launching local mode without `model.safetensors` file,
the original code will result `discard_names = []` when
`hf_hub_download` throws an connection error.
```python
# server/text_generation_server/cli.py
    try:
        import transformers
        import json
    
    
        config_filename = hf_hub_download(model_id, revision=revision, filename="config.json")
        with open(config_filename, "r") as f:
            config = json.load(f)
        architecture = config["architectures"][0]
    
        class_ = getattr(transformers, architecture)
    
        # Name for this varible depends on transformers version.
        discard_names = getattr(class_, "_tied_weights_keys", [])
        discard_names.extend(getattr(class_, "_keys_to_ignore_on_load_missing", []))
    
    except Exception as e:
        discard_names = []
```

The expected `_tied_weights_keys` of OPT-1.3b is `["lm_head.weight"]`,
and its tied weight `"model.decoder.embed_tokens.weight"` will be kept
in the safetensors conversion. But the above empty `discard_names` will
lead to `"lm_head.weight"` being kept and
`"model.decoder.embed_tokens.weight"` being discard in the subsequent
method `_remove_duplicate_names`, which causes error #1057.

So add a local mode branch to get the expected `discard_names` like
follows. This modification also applies to other models

```python
# server/text_generation_server/cli.py
        if is_local_model:
            config_filename = os.path.join(model_id, "config.json")
        else:
            config_filename = hf_hub_download(model_id, revision=revision, filename="config.json")
```


In addition, when `_tied_weights_keys` or
`_keys_to_ignore_on_load_missing` is `None`, the above code will also
throw an error unexpectedly. This is fixed in PR #1052


## Before submitting
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N/A
- [ ] Did you write any new necessary tests?  N/A


## Who can review?

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@Narsil
2023-09-26 14:57:53 +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?

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---------



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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
Nicolas Patry 0a63e9ab68
Fix __call__ vs forward. (#993)
# What does this PR do?

Fix __call__ vs forward.

To reproduce error just launch:
TheBloke/WizardLM-Uncensored-Falcon-7B-GPTQ with gptq (it fails because
falcon code uses `__call__` instead for `forward` calls)

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2023-09-07 17:36:30 +02:00
Florian Zimmermeister b03d2621a7
add transformers gptq support (#963)
Proposal to fix
https://github.com/huggingface/text-generation-inference/issues/962
2023-09-07 10:19:42 +02:00
Maxime Laboissonnière 935a77fb74
Fix exllama wronfully loading (#990)
# What does this PR do?
The
[changes](https://github.com/huggingface/text-generation-inference/pull/986/files#diff-b72e45030214e50c8ff6e3be837057b3f3368b9779fd942ca680f949fe069eafR176)
disabling exllama on old compute had unintended consequences of not
setting `use_exllama` to `False` if `HAS_EXLLAMA` equals `False` **and**
`CAN_EXLLAMA` equals `False`. This fixes this.

## Before submitting
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2023-09-07 09:17:22 +02:00
Nicolas Patry 211e7b7e35
Disabling exllama on old compute. (#986)
# What does this PR do?

Disabling exllama on old compute.

Exllama + T4 don't play nice together, this will disable it right away
to avoid issues at runtime.

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2023-09-06 15:01:00 +02:00
Nicolas Patry 033230ae66
Backport https://github.com/vllm-project/vllm/pull/936 (#977)
# What does this PR do?

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2023-09-04 15:00:19 +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
Nicolas Patry 4f5d93ecd0
Fixing top_k tokens when k ends up < 0 (#966)
# What does this PR do?

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2023-09-01 00:22:03 +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 5485c142e8
New release. (#941)
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2023-08-29 14:28:22 +02:00
Nicolas Patry 211b54ac41
Rebased #617 (#868)
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Co-authored-by: Vincent Brouwers <vincent.brouwers@ing.com>
2023-08-28 11:43:47 +02:00
Nicolas Patry 4486f78cf9
Fixing the lora adaptation on docker. (#935)
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2023-08-28 11:13:24 +02:00
Nicolas Patry e605c2a43e
Supporting code llama. (#918)
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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
Nicolas Patry 2774b0ab44
Fixing watermark. (#851)
# What does this PR do?

Fixes #843 
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2023-08-16 07:17:26 +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 b5087c4f4e
Fix rope dynamic + factor (#822)
# What does this PR do?

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Fixes #816

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2023-08-14 14:09:51 +02:00
Nicolas Patry 09eca64227
Version 1.0.1 (#836)
# What does this PR do?

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2023-08-14 11:23:11 +02:00
Nicolas Patry cc7bb5084d
Upgrade transformers (fix protobuf==3.20 issue) (#795)
# What does this PR do?

Fixes #531

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2023-08-11 16:46:08 +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 1fdc88ee90
Fixing non 4bits quantization. (#785)
# What does this PR do?

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Fixes #784 

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2023-08-07 13:02:00 +02:00
Nicolas Patry 891e19cc51
Fix dynamic rope. (#783)
# What does this PR do?

Typo

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2023-08-07 12:28:19 +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
zspo f91e9d282d
fix build tokenizer in quantize and remove duplicate import (#768)
# What does this PR do?

Fixes #732 
And remove duplicate AutoTokenizer import

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2023-08-03 22:21:33 +02:00
Nicolas Patry 6ec5288ab7
This should prevent the PyTorch overriding. (#767)
# What does this PR do?

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2023-08-03 21:54:39 +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
Nicolas Patry d3d8f1bd6b
Typo fix. (#746)
# What does this PR do?

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2023-07-31 18:57:29 +02:00
Nicolas Patry 15fc64668f
fix(server): Failing quantize config after local read. (#743)
# What does this PR do?

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2023-07-31 17:51:26 +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


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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.

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CC @OlivierDehaene
2023-07-31 14:35:14 +02:00
Nicolas Patry 92bb56b0c1
Local gptq support. (#738)
# What does this PR do?

Redoes #719

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2023-07-31 10:32:52 +02:00
OlivierDehaene 3ef5ffbc64
v1.0.0 (#727) 2023-07-28 17:43:46 +02:00
OlivierDehaene afd04dc71e
feat(server): update vllm version (#723) 2023-07-28 15:36:38 +02:00
OlivierDehaene 9f18f4c006
v0.9.4 (#713) 2023-07-27 19:25:15 +02:00
OlivierDehaene ab96b9aec3
feat(server): support new falcon config (#712) 2023-07-27 18:38:57 +02:00
OlivierDehaene 2efd46ef95 fix(server): fix missing datasets in quantize 2023-07-27 14:50:45 +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.


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2023-07-25 13:00:27 +02:00
OlivierDehaene 37df6df38e
fix(server): fix exllama buffers (#689)
Close #683
2023-07-24 14:25:43 +02:00
OlivierDehaene 73a4d65d26
feat: add cuda memory fraction (#659)
Close #673
2023-07-24 11:43:58 +02:00