Commit Graph

18 Commits

Author SHA1 Message Date
Nicolas Patry 211b211ec0
feat(server): add support for llamav2 (#633) 2023-07-18 18:09:53 +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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---------

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 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 e3e487dc71
feat(server): support trust_remote_code (#363) 2023-05-23 20:40:39 +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 d7a97aa0b6
Removing dead variables. (#327)
# What does this PR do?

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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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2023-05-15 11:32:25 +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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2023-05-12 14:46:41 +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 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
OlivierDehaene e14ae3b5e9
feat(server): support quantization for flash models (#200)
closes #197
2023-04-19 12:51:11 +02:00
OlivierDehaene 299217c95c
feat(server): add flash attention llama (#144) 2023-04-11 16:38:22 +02:00