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179 Commits

Author SHA1 Message Date
Nicolas Patry 986b4044d1
Phi3 support (#1797)
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2024-04-23 18:40:05 +02:00
Nicolas Patry f9ee2c41b9
Upgrading all versions. (#1759) 2024-04-18 17:17:40 +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
Nicolas Patry 408dbc485c
Fp8 Support (#1726)
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---------

Co-authored-by: Dong Shin <d0104.shin@gmail.com>
2024-04-12 08:13:30 +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 8dca3b04f8
Force weights_only (before fully breaking pickle files anyway). (#1710)
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2024-04-05 19:23:57 +02:00
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
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 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 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
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 fa8a8e05af
fix(router): fix openapi and add jsonschema validation (#1578) 2024-02-21 11:05:32 +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
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)
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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
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 b95732180d
Reinstate exl2 with tp (#1490)
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2024-01-26 14:00:29 +01:00
Nicolas Patry 7e542d4d05
Fixing non divisible embeddings. (#1476)
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2024-01-24 13:08:41 +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 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 82670d9786
feat: add quant to mixtral (#1337) 2023-12-12 17:55:03 +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
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
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.


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@Narsil
2023-11-23 12:41:05 +01:00
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
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 85acb11ba0
Handling bloom prefix. (#1090)
# What does this PR do?

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2023-10-03 11:55:10 +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 


## Before submitting
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other checks if that's the case).
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2023-10-02 20:53:14 +02:00
OlivierDehaene 3b56d7669b
feat: add mistral model (#1071) 2023-09-28 09:55:47 +02:00
OlivierDehaene 47954b81e9
feat: format code (#1070) 2023-09-27 12:22:09 +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 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

---------



# What does this PR do?

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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
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.

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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 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
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 bce5e22444
Adding Idefics multi modal model. (#842)
Co-Authored-By: Victor Sanh <victorsanh@gmail.com>


# What does this PR do?

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Co-authored-by: Victor Sanh <victorsanh@gmail.com>
2023-08-17 14:38:49 +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
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 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 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
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
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
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 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
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
Nicolas Patry 08b8eec1d7
fix(server): Fixing non parameters in quantize script `bigcode/starcoder` was an example. (#661) 2023-07-20 16:04:15 +02:00
cdawg 214c06f510
Add trust_remote_code to quantize script (#647)
# What does this PR do?

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Fixes a bug appeared with MR #587 fixing issue #552.
See the discussion in #552.

With MR #587 the trust_remote_code variable is not passed to
AutoModelForCausalLM, but is found in the function signature. This
prevents models like falcon to be quantized, because trust_remote_code
is required. This MR fixes the issue.


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2023-07-20 13:53:08 +02:00
OlivierDehaene 3b71c38558
feat(server): flash attention v2 (#624) 2023-07-18 16:21:18 +02:00
Nicolas Patry 4d38a1c4ad
feat(server): Reworking the quantization script so it's still universal (not llama specific) (#587)
but should work on more configurations (no need for 2 GPUs, less RAM
usage).


# What does this PR do?

Reworking the quantization script so it's still universal (not llama
specific)

but should work on more configurations (no need for 2 GPUs, less RAM
usage).

Still need to investigate the potential differences in quantization
results.


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2023-07-18 12:19:05 +02:00
OlivierDehaene 5b9de4a1d3
fix(server): blacklist local files (#609)
Close #589 #602
2023-07-13 21:54:55 +02:00
ssmi153 3628559516
GPTQ Env vars: catch correct type of error (#596)
# What does this PR do?

When passing in environment variables like gptq_bits, we still get
errors thrown from TGI because the try/catch block is catching the wrong
type of error. This PR aims to fix that.

@Narsil - let me know if this is how you want this formatted. My Python
is a little shaky, so I hope this syntax is correct.
2023-07-12 19:57:46 +02:00
Nicolas Patry 67347950b7
feat(server): Implements sharding for non divisible `vocab_size`. (#583)
- The code is relatively easy (just disable the checks on Embedding and
Head)

This cannot be done in the same easy fashion for hidden_dim/head_dim.
It's relatively easy on some models (classic MHA) but it would make the
other
models (MQA) much more complex, and GPTQ quantization another quite
hairy piece
of code.
2023-07-12 16:43:31 +02:00
ssmi153 2c4bf88268
fix(server): Bug fixes for GPTQ_BITS environment variable passthrough (#590)
# What does this PR do?

This fixes a typo and extends the GPTP_BITS environment variables
through to the second method which requires the same logic. Please let
me know if there's anything I've misunderstood in this change.

Thanks @Narsil for the original fix.
2023-07-12 14:17:35 +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 e943a294bc
fix(server): harden the weights choice to save on disk. (#561)
- Look at `transformers` base class to check for
  `_key_to_ignore_on_load_missing` or `_tied_weights` which are the
  standard attributes to select the keys to NOT save on disk (since they
  are ignored)

- Modified safetensors code (to be reflected in safetensors even if it's
  an internal function).
  
- Will not work for trust_remote_code=True repos (like santacoder).

Should help with :
https://github.com/huggingface/text-generation-inference/issues/555
and : https://github.com/huggingface/text-generation-inference/pull/501
and https://github.com/huggingface/text-generation-inference/issues/556
and
https://github.com/huggingface/text-generation-inference/issues/482#issuecomment-1623713593
2023-07-07 14:50:12 +02:00
OlivierDehaene 31e2253ae7
feat(server): use latest flash attention commit (#543)
@njhill FYI
2023-07-04 20:23:55 +02:00
Nick Hill e4b26aa10b
fix(server): avoid errors for very small top_p values (#544)
See https://github.com/huggingface/transformers/pull/24111

I didn't add validation to the `__init__` method since it's not done for
other values/warpers.
2023-07-04 20:11:33 +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
OlivierDehaene e74bd41e0f
feat(server): add paged attention to flash models (#516)
Closes #478
2023-06-30 19:09:59 +02:00
Antoni Baum ae466a8736
fix(server): Do not init process group if already initialized (#388) 2023-06-26 12:32:54 +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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---------

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