Commit Graph

22 Commits

Author SHA1 Message Date
Daniël de Kok 093a27c528
Add support for GPTQ Marlin (#2052)
Add support for GPTQ Marlin kernels

GPTQ Marlin extends the Marlin kernels to support common GPTQ
configurations:

- bits: 4 or 8
- groupsize: -1, 32, 64, or 128
- desc_act: true/false

Using the GPTQ Marlin kernels requires repacking the parameters in the
Marlin quantizer format.

The kernels were contributed by Neural Magic to VLLM. We vendor them
here for convenience.
2024-06-14 09:45:42 +02:00
OlivierDehaene 521de6cacd
fix(server): fix OPT implementation (#2061) 2024-06-12 18:22:20 +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
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 44b267ab22 fix: fix gpt-q params loading 2023-12-14 11:02:16 +01:00
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
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
Nicolas Patry ecf6dc3a5a
feat: Add the option to force another dtype than `f16`. (#513) 2023-06-30 20:30:09 +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 337afb2842
fix(server): fix bnb quantization for CausalLM models (#385) 2023-05-31 11:48:28 +02:00
OlivierDehaene e3e487dc71
feat(server): support trust_remote_code (#363) 2023-05-23 20:40:39 +02:00
OlivierDehaene 91d9beec90
fix(server): fix init for flash causal lm (#352)
Fixes #347
2023-05-22 15:05:32 +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)
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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
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 85aa7e2e7b
feat(server): support hf endpoint weight layout (#266) 2023-05-03 11:36:24 +02:00
OlivierDehaene 343437c7b5
feat(router): add device and dtype info (#215) 2023-04-21 15:36:29 +02:00
OlivierDehaene 880a76eed5
feat(server): support sharded santacoder (#167) 2023-04-12 17:18:08 +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