riaz.somc/transformers
1
0
Fork 0
mirror of https://github.com/huggingface/transformers.git synced 2025-07-04 05:10:06 +06:00
Code Issues Actions 20 Packages Projects Releases Wiki Activity
beaed8ce01
transformers/docs/source/en/main_classes/quantization.md
Mohamed Mekkouri b262680af4
Add Bitnet model (#37742) 
* Adding BitNet b1.58 Model

* Add testing code for BitNet

* Fix format issues

* Fix docstring format issues

* Fix docstring

* Fix docstring

* Fix: weight back to uint8

* Fix

* Fix format issues

* Remove copy comments

* Add model link to the docstring

* Fix: set tie_word_embeddings default to false

* Update

* Generate modeling file

* Change config name for automatically generating modeling file.

* Generate modeling file

* Fix class name

* Change testing branch

* Remove unused param

* Fix config docstring

* Add docstring for BitNetQuantConfig.

* Fix docstring

* Update docs/source/en/model_doc/bitnet.md

Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>

* Update docs/source/en/model_doc/bitnet.md

Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Update bitnet config

* Update explanation between online and offline mode

* Remove space

* revert changes

* more revert

* spaces

* update

* fix-copies

* doc fix

* fix minor nits

* empty

* small nit

* empty

---------

Co-authored-by: Shuming Ma <shumingma@pku.edu.cn>
Co-authored-by: shumingma <shmingm@gmail.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
2025-04-28 15:08:46 +02:00

2.1 KiB
Executable File
Raw Blame History

Quantization

Quantization techniques reduce memory and computational costs by representing weights and activations with lower-precision data types like 8-bit integers (int8). This enables loading larger models you normally wouldn't be able to fit into memory, and speeding up inference. Transformers supports the AWQ and GPTQ quantization algorithms and it supports 8-bit and 4-bit quantization with bitsandbytes.

Quantization techniques that aren't supported in Transformers can be added with the [HfQuantizer] class.

Learn how to quantize models in the Quantization guide.

QuantoConfig

autodoc QuantoConfig

AqlmConfig

autodoc AqlmConfig

VptqConfig

autodoc VptqConfig

AwqConfig

autodoc AwqConfig

EetqConfig

autodoc EetqConfig

GPTQConfig

autodoc GPTQConfig

BitsAndBytesConfig

autodoc BitsAndBytesConfig

HfQuantizer

autodoc quantizers.base.HfQuantizer

HiggsConfig

autodoc HiggsConfig

HqqConfig

autodoc HqqConfig

FbgemmFp8Config

autodoc FbgemmFp8Config

CompressedTensorsConfig

autodoc CompressedTensorsConfig

TorchAoConfig

autodoc TorchAoConfig

BitNetQuantConfig

autodoc BitNetQuantConfig

SpQRConfig

autodoc SpQRConfig

FineGrainedFP8Config

autodoc FineGrainedFP8Config

QuarkConfig

autodoc QuarkConfig

AutoRoundConfig

autodoc AutoRoundConfig