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* add codegemma example in GPU/HF-Transformers-AutoModels/ * add README of codegemma example in GPU/HF-Transformers-AutoModels/ * add codegemma example in GPU/PyTorch-Models/ * add readme of codegemma example in GPU/PyTorch-Models/ * add codegemma example in CPU/HF-Transformers-AutoModels/ * add readme of codegemma example in CPU/HF-Transformers-AutoModels/ * add codegemma example in CPU/PyTorch-Models/ * add readme of codegemma example in CPU/PyTorch-Models/ * fix typos * fix filename typo * add codegemma in tables * add comments of lm_head * remove comments of use_cache |
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| bark | ||
| bert | ||
| bluelm | ||
| chatglm | ||
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| codegemma | ||
| codellama | ||
| codeshell | ||
| deciLM-7b | ||
| deepseek | ||
| deepseek-moe | ||
| distil-whisper | ||
| flan-t5 | ||
| fuyu | ||
| internlm-xcomposer | ||
| internlm2 | ||
| llama2 | ||
| llama3 | ||
| llava | ||
| mamba | ||
| meta-llama | ||
| mistral | ||
| mixtral | ||
| openai-whisper | ||
| phi-1_5 | ||
| phi-2 | ||
| phi-3 | ||
| phixtral | ||
| qwen-vl | ||
| qwen1.5 | ||
| skywork | ||
| solar | ||
| stablelm | ||
| wizardcoder-python | ||
| yi | ||
| yuan2 | ||
| ziya | ||
| README.md | ||
IPEX-LLM INT4 Optimization for Large Language Model
You can use optimize_model API to accelerate general PyTorch models on Intel servers and PCs. This directory contains example scripts to help you quickly get started using IPEX-LLM to run some popular open-source models in the community. Each model has its own dedicated folder, where you can find detailed instructions on how to install and run it.
Recommended Requirements
To run the examples, we recommend using Intel® Xeon® processors (server), or >= 12th Gen Intel® Core™ processor (client).
For OS, IPEX-LLM supports Ubuntu 20.04 or later, CentOS 7 or later, and Windows 10/11.
Best Known Configuration on Linux
For better performance, it is recommended to set environment variables on Linux with the help of IPEX-LLM:
pip install ipex-llm
source ipex-llm-init