id stringlengths 16 145 | text stringlengths 1 179k | title stringclasses 1
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|---|---|---|
hugging_face/hfquantizer_51_0.txt | Join the Hugging Face community | |
hugging_face/495_70_0.txt | --- | |
hugging_face/hfquantizer_79_0.txt | 8. Add tests! You should add tests by first adding the package in our nightly Dockerfile inside ` docker/transformers-quantization-latest-gpu ` and then adding a new test file in ` tests/quantization/xxx ` . Feel free to check out how it is implemented for other quantization methods. | |
hugging_face/modelquantizationwit_82_0.txt | [ Model Quantization ](/tag/model-quantization?source=post_page-----
b4c9983e8996---------------model_quantization-----------------) | |
hugging_face/495_55_0.txt | Closed | |
hugging_face/quantization_141_0.txt | ## HfQuantizer | |
hugging_face/quantization_31_0.txt | Contribute | |
hugging_face/quantization_16_0.txt | Natural Language Processing | |
hugging_face/modelquantizationwit_67_0.txt | One advanced use case involves loading a model and distributing weights
between the CPU and GPU. This can be achieved by setting `
llm_int8_enable_fp32_cpu_offload=True ` . This feature is beneficial for users
who need to fit large models and distribute them between the GPU and CPU. | |
hugging_face/hfquantizer_35_0.txt | API | |
hugging_face/modelquantizationwit_76_0.txt | Reference Links: | |
hugging_face/modelquantizationwit_98_0.txt | Help | |
hugging_face/495_82_0.txt | Sorry, something went wrong. | |
hugging_face/quantization_65_0.txt | Parameters | |
hugging_face/495_89_0.txt | --- | |
hugging_face/quantization_51_0.txt | and get access to the augmented documentation experience | |
hugging_face/modelquantizationwit_37_0.txt | ## Loading a Model in 8-bit Quantization | |
hugging_face/495_149_0.txt | No milestone | |
hugging_face/495_154_0.txt | ## Footer | |
hugging_face/495_67_0.txt | tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=True,cache_dir='../model')
tokenizer.pad_token = tokenizer.eos_token | |
hugging_face/modelquantizationwit_51_0.txt | The NF4 data type is designed for weights initialized using a normal
distribution. You can use it by specifying ` bnb_4bit_quant_type="nf4" ` : | |
hugging_face/495_139_0.txt | All reactions | |
hugging_face/495_63_0.txt | ### | |
hugging_face/hfquantizer_14_0.txt | [ Run inference with pipelines
](/docs/transformers/main/en/pipeline_tutorial) [ Write portable code with
AutoClass ](/docs/transformers/main/en/autoclass_tutorial) [ Preprocess data
](/docs/transformers/main/en/preprocessing) [ Fine-tune a pretrained model
](/docs/transformers/main/en/training) [ Train with a script
... | |
hugging_face/hfquantizer_46_0.txt | Graph models | |
hugging_face/quantization_15_0.txt | Task Guides | |
hugging_face/hfquantizer_63_0.txt | * The quantization method is available through a Python package that is pip-installable by anyone (it is also fine if you can only install the package from source). Ideally, pre-compiled kernels are included in the pip package.
* The method can run on commonly-used hardware (CPU, GPU, …).
* The method is wrapped in a `... | |
hugging_face/modelquantizationwit_97_0.txt | [
](/m/signin?actionUrl=%2F_%2Fapi%2Fsubscriptions%2Fnewsletters%2F1baa47f8bb11&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40rakeshrajpurohit%2Fmodel-
quantization-with-hugging-face-transformers-and-bitsandbytes-
integration-b4c9983e8996&newsletterV3=67d4227cd655&newsletterV3Id=1baa47f8bb11&user=Rakesh+Raj... | |
hugging_face/modelquantizationwit_95_0.txt | [ https://www.linkedin.com/in/rakeshrajpurohit/
](https://www.linkedin.com/in/rakeshrajpurohit/) Expert in NLP and Machine
Learning, and Driving AI product development | |
hugging_face/quantization_34_0.txt | [ Philosophy ](/docs/transformers/en/philosophy) [ Glossary
](/docs/transformers/en/glossary) [ What 🤗 Transformers can do
](/docs/transformers/en/task_summary) [ How 🤗 Transformers solve tasks
](/docs/transformers/en/tasks_explained) [ The Transformer model family
](/docs/transformers/en/model_summary) [ Summary of... | |
hugging_face/hfquantizer_39_0.txt | Text models | |
hugging_face/quantization_163_0.txt | ( *args **kwargs ) | |
hugging_face/quantization_85_0.txt | [ < source >
](https://github.com/huggingface/transformers/blob/v4.40.1/src/transformers/utils/quantization_config.py#L626) | |
hugging_face/quantization_46_0.txt | Graph models | |
hugging_face/hugging_face_3_1.txt | b documentation
The Hugging Face Hub is a platform with over 350k models, 75k datasets, and
150k demo apps (Spaces), all open source and publicly available, in an online
platform where people can easily collaborate and build ML together. The Hub
works as a central place where anyone can explore, experiment, collaborat... | |
hugging_face/495_4_0.txt | [ Sign in
](/login?return_to=https%3A%2F%2Fgithub.com%2Fstanfordnlp%2Fdspy%2Fissues%2F495) | |
hugging_face/quantization_63_0.txt | [ < source >
](https://github.com/huggingface/transformers/blob/v4.40.1/src/transformers/utils/quantization_config.py#L857) | |
hugging_face/quantization_123_0.txt | [ < source >
](https://github.com/huggingface/transformers/blob/v4.40.1/src/transformers/utils/quantization_config.py#L349) | |
hugging_face/hfquantizer_61_0.txt | ## Requirements | |
hugging_face/495_59_0.txt | [ adapters ](/stanfordnlp/dspy/labels/adapters) Adapters and Integrations to
other libraries | |
hugging_face/modelquantizationwit_78_0.txt | [ https://huggingface.co/docs/transformers/main_classes/quantization
](https://huggingface.co/docs/transformers/main_classes/quantization) | |
hugging_face/modelquantizationwit_85_0.txt | \-- | |
hugging_face/495_2_0.txt | Toggle navigation | |
hugging_face/modelquantizationwit_19_0.txt | Share | |
hugging_face/495_1_0.txt | ## Navigation Menu | |
hugging_face/quantization_4_0.txt | Transformers documentation | |
hugging_face/495_148_0.txt | Milestone | |
hugging_face/modelquantizationwit_107_0.txt | ](https://blog.medium.com/?source=post_page-----
b4c9983e8996--------------------------------) | |
hugging_face/hugging_face_4_5.txt | les/training/sts/README.html)
* [ Training data ](examples/training/sts/README.html#training-data)
* [ Loss Function ](examples/training/sts/README.html#loss-function)
* [ Natural Language Inference ](examples/training/nli/README.html)
* [ Data ](examples/training/nli/README.html#data)
* [ SoftmaxLoss... | |
hugging_face/quantization_104_0.txt | Get compatible class with optimum gptq config dict | |
hugging_face/hugging_face_3_3.txt | repositories** ](./organizations-security) , and manage their organization’s [
payment method and billing info ](https://huggingface.co/pricing) . Machine
Learning is more fun when collaborating! 🔥
[ Explore existing organizations ](https://huggingface.co/organizations) ,
create a new organization [ here ](https://hu... | |
hugging_face/quantization_201_0.txt | #### validate_environment | |
hugging_face/hfquantizer_33_0.txt | Conceptual guides | |
hugging_face/modelquantizationwit_46_0.txt | ## Changing the Compute Data Type | |
hugging_face/quantization_14_0.txt | [ Run inference with pipelines ](/docs/transformers/en/pipeline_tutorial) [
Write portable code with AutoClass
](/docs/transformers/en/autoclass_tutorial) [ Preprocess data
](/docs/transformers/en/preprocessing) [ Fine-tune a pretrained model
](/docs/transformers/en/training) [ Train with a script
](/docs/transformers... | |
hugging_face/hfquantizer_76_0.txt | 5. Write the ` _process_model_before_weight_loading ` method. In Transformers, the quantized models are initialized first on the ` "meta" ` device before loading the weights. This means the ` _process_model_before_weight_loading ` method takes care of manipulating the model skeleton to replace some modules (e.g., ` nn.... | |
hugging_face/hfquantizer_62_0.txt | Before integrating a new quantization method into Transformers, ensure the
method you are trying to add meets the following prerequisites. Only
quantization methods that can be run with PyTorch modules are currently
supported. | |
hugging_face/quantization_102_0.txt | [ < source >
](https://github.com/huggingface/transformers/blob/v4.40.1/src/transformers/utils/quantization_config.py#L611) | |
hugging_face/495_92_0.txt | [ 
](/ujjawal-ti) | |
hugging_face/hfquantizer_65_0.txt | class Linear4bit(nn.Module):
def __init__(self, ...):
... | |
hugging_face/modelquantizationwit_66_0.txt | ## Offloading Between CPU and GPU | |
hugging_face/quantization_192_0.txt | Parameters | |
hugging_face/modelquantizationwit_29_0.txt | pip install git+https://github.com/huggingface/transformers.git | |
hugging_face/quantization_37_0.txt | [ Agents and Tools ](/docs/transformers/en/main_classes/agent) [ Auto Classes
](/docs/transformers/en/model_doc/auto) [ Backbones
](/docs/transformers/en/main_classes/backbones) [ Callbacks
](/docs/transformers/en/main_classes/callback) [ Configuration
](/docs/transformers/en/main_classes/configuration) [ Data Collato... | |
hugging_face/quantization_27_0.txt | [ Methods and tools for efficient training on a single GPU
](/docs/transformers/en/perf_train_gpu_one) [ Multiple GPUs and parallelism
](/docs/transformers/en/perf_train_gpu_many) [ Fully Sharded Data Parallel
](/docs/transformers/en/fsdp) [ DeepSpeed ](/docs/transformers/en/deepspeed)
[ Efficient training on CPU ](/... | |
hugging_face/quantization_94_0.txt | ## GPTQConfig | |
hugging_face/modelquantizationwit_77_0.txt | [ https://huggingface.co/docs/optimum/concept_guides/quantization
](https://huggingface.co/docs/optimum/concept_guides/quantization) | |
hugging_face/modelquantizationwit_110_0.txt | Terms | |
hugging_face/quantization_187_0.txt | * **device_map** ( ` Union[dict, str] ` , _optional_ ) — The device_map that is passed through the ` from_pretrained ` method. | |
hugging_face/quantization_13_0.txt | Tutorials | |
hugging_face/quantization_80_0.txt | [ < source >
](https://github.com/huggingface/transformers/blob/v4.40.1/src/transformers/utils/quantization_config.py#L835) | |
hugging_face/quantization_156_0.txt | Override this method if you want to adjust the ` target_dtype ` variable used
in ` from_pretrained ` to compute the device_map in case the device_map is a `
str ` . E.g. for bitsandbytes we force-set ` target_dtype ` to ` torch.int8 `
and for 4-bit we pass a custom enum ` accelerate.CustomDtype.int4 ` . | |
hugging_face/hfquantizer_18_0.txt | Computer Vision | |
hugging_face/495_95_0.txt | ### | |
hugging_face/hfquantizer_28_0.txt | Optimizing inference | |
hugging_face/hfquantizer_13_0.txt | Tutorials | |
hugging_face/quantization_144_0.txt | ( quantization_config : QuantizationConfigMixin **kwargs ) | |
hugging_face/modelquantizationwit_53_0.txt | nf4_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4") | |
hugging_face/quantization_175_0.txt | * **model** ( ` ~transformers.PreTrainedModel ` ) — The model to quantize
* **kwargs** ( ` dict ` , _optional_ ) — The keyword arguments that are passed along ` _process_model_after_weight_loading ` . | |
hugging_face/495_88_0.txt | Yup! Their documentation on [ quantization ](https://huggingface.co/docs/text-
generation-inference/en/conceptual/quantization) should be helpful. | |
hugging_face/quantization_22_0.txt | Developer guides | |
hugging_face/modelquantizationwit_115_0.txt | ](/business?source=post_page-----b4c9983e8996--------------------------------) | |
hugging_face/hfquantizer_70_0.txt | ## Build a new HFQuantizer class | |
hugging_face/495_61_0.txt | [ 
](/ujjawal-ti) | |
hugging_face/modelquantizationwit_41_0.txt | tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", load_in_8bit=True) | |
hugging_face/hugging_face_4_3.txt | l#symmetric-vs-asymmetric-semantic-search)
* [ Python ](examples/applications/semantic-search/README.html#python)
* [ util.semantic_search ](examples/applications/semantic-search/README.html#util-semantic-search)
* [ Speed Optimization ](examples/applications/semantic-search/README.html#speed-optimization)
... | |
hugging_face/495_46_0.txt | New issue | |
hugging_face/hfquantizer_68_0.txt | * The quantization method should be serializable. You can save the quantized weights locally or push them to the Hub.
* Make sure the package that contains the quantization kernels/primitive is stable (no frequent breaking changes). | |
hugging_face/modelquantizationwit_74_0.txt | # Conclusion | |
hugging_face/modelquantizationwit_84_0.txt | [
](/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2F_%2Fvote%2Fp%2Fb4c9983e8996&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40rakeshrajpurohit%2Fmodel-
quantization-with-hugging-face-transformers-and-bitsandbytes-
integration-b4c9983e8996&user=Rakesh+Rajpurohit&userId=67d4227cd655&source=-----b4c9983e8996
--... | |
hugging_face/hfquantizer_37_0.txt | [ Agents and Tools ](/docs/transformers/main/en/main_classes/agent) [ Auto
Classes ](/docs/transformers/main/en/model_doc/auto) [ Backbones
](/docs/transformers/main/en/main_classes/backbones) [ Callbacks
](/docs/transformers/main/en/main_classes/callback) [ Configuration
](/docs/transformers/main/en/main_classes/con... | |
hugging_face/495_132_0.txt | llm.model = prepare_model_for_kbit_training(llm.model)
llm.model = get_peft_model(llm.model, config)
######################################### | |
hugging_face/modelquantizationwit_17_0.txt | [
](/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2F_%2Fbookmark%2Fp%2Fb4c9983e8996&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40rakeshrajpurohit%2Fmodel-
quantization-with-hugging-face-transformers-and-bitsandbytes-
integration-b4c9983e8996&source=-----b4c9983e8996---------------------
bookmark_footer-----... | |
hugging_face/495_79_0.txt | 👍 1 arnavsinghvi11 reacted with thumbs up emoji | |
hugging_face/quantization_205_0.txt | [ < > Update on GitHub
](https://github.com/huggingface/transformers/blob/main/docs/source/en/main_classes/quantization.md) | |
hugging_face/quantization_30_0.txt | [ Instantiate a big model ](/docs/transformers/en/big_models) [ Debugging
](/docs/transformers/en/debugging) [ XLA Integration for TensorFlow Models
](/docs/transformers/en/tf_xla) [ Optimize inference using `torch.compile()`
](/docs/transformers/en/perf_torch_compile) | |
hugging_face/495_108_0.txt | --- | |
hugging_face/495_141_0.txt | [ Sign up for free ](/join?source=comment-repo) **to join this conversation on
GitHub** . Already have an account? [ Sign in to comment
](/login?return_to=https%3A%2F%2Fgithub.com%2Fstanfordnlp%2Fdspy%2Fissues%2F495) | |
hugging_face/hfquantizer_47_0.txt | Internal Helpers | |
hugging_face/quantization_128_0.txt | ( ) |
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