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A Python package for extending the official PyTorch that can easily obtain performance on Intel platform

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Intel® Extension for PyTorch*

CPU 💻main branch   |   🌱Quick Start   |   📖Documentations   |   🏃Installation   |   💻LLM Example
GPU 💻main branch   |   🌱Quick Start   |   📖Documentations   |   🏃Installation   |   💻LLM Example

Intel® Extension for PyTorch* extends PyTorch* with up-to-date features optimizations for an extra performance boost on Intel hardware. Optimizations take advantage of Intel® Advanced Vector Extensions 512 (Intel® AVX-512) Vector Neural Network Instructions (VNNI) and Intel® Advanced Matrix Extensions (Intel® AMX) on Intel CPUs as well as Intel Xe Matrix Extensions (XMX) AI engines on Intel discrete GPUs. Moreover, Intel® Extension for PyTorch* provides easy GPU acceleration for Intel discrete GPUs through the PyTorch* xpu device.

ipex.llm - Large Language Models (LLMs) Optimization

In the current technological landscape, Generative AI (GenAI) workloads and models have gained widespread attention and popularity. Large Language Models (LLMs) have emerged as the dominant models driving these GenAI applications. Starting from 2.1.0, specific optimizations for certain LLM models are introduced in the Intel® Extension for PyTorch*. Check LLM optimizations for details.

Optimized Model List

MODEL FAMILY MODEL NAME (Huggingface hub) FP32 BF16 Static quantization INT8 Weight only quantization INT8 Weight only quantization INT4
LLAMA meta-llama/Llama-2-7b-hf 🟩 🟩 🟩 🟩 🟨
LLAMA meta-llama/Llama-2-13b-hf 🟩 🟩 🟩 🟩 🟨
LLAMA meta-llama/Llama-2-70b-hf 🟩 🟩 🟩 🟩 🟨
GPT-J EleutherAI/gpt-j-6b 🟩 🟩 🟩 🟩 🟩
GPT-NEOX EleutherAI/gpt-neox-20b 🟩 🟨 🟨 🟩 🟨
DOLLY databricks/dolly-v2-12b 🟩 🟨 🟨 🟩 🟨
FALCON tiiuae/falcon-40b 🟩 🟩 🟩 🟩 🟩
OPT facebook/opt-30b 🟩 🟩 🟩 🟩 🟨
OPT facebook/opt-1.3b 🟩 🟩 🟩 🟩 🟨
Bloom bigscience/bloom-1b7 🟩 🟨 🟩 🟩 🟨
CodeGen Salesforce/codegen-2B-multi 🟩 🟩 🟨 🟩 🟩
Baichuan baichuan-inc/Baichuan2-7B-Chat 🟩 🟩 🟩 🟩
Baichuan baichuan-inc/Baichuan2-13B-Chat 🟩 🟩 🟩 🟩
Baichuan baichuan-inc/Baichuan-13B-Chat 🟩 🟨 🟩 🟩
ChatGLM THUDM/chatglm3-6b 🟩 🟩 🟨 🟩
ChatGLM THUDM/chatglm2-6b 🟩 🟩 🟨 🟩
GPTBigCode bigcode/starcoder 🟩 🟩 🟨 🟩 🟨
T5 google/flan-t5-xl 🟩 🟩 🟨 🟩
Mistral mistralai/Mistral-7B-v0.1 🟩 🟩 🟨 🟩 🟨
MPT mosaicml/mpt-7b 🟩 🟩 🟨 🟩 🟩
  • 🟩 signifies that the model can perform well and with good accuracy (<1% difference as compared with FP32).

  • 🟨 signifies that the model can perform well while accuracy may not been in a perfect state (>1% difference as compared with FP32).

Note: The above verified models (including other models in the same model family, like "codellama/CodeLlama-7b-hf" from LLAMA family) are well supported with all optimizations like indirect access KV cache, fused ROPE, and prepacked TPP Linear (fp32/bf16). We are working in progress to better support the models in the tables with various data types. In addition, more models will be optimized in the future.

Support

The team tracks bugs and enhancement requests using GitHub issues. Before submitting a suggestion or bug report, search the existing GitHub issues to see if your issue has already been reported.

License

Apache License, Version 2.0. As found in LICENSE file.

Security

See Intel's Security Center for information on how to report a potential security issue or vulnerability.

See also: Security Policy

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A Python package for extending the official PyTorch that can easily obtain performance on Intel platform

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