* axolotl_quickstart.md * benchmark_quickstart.md * bigdl_llm_migration.md * chatchat_quickstart.md * continue_quickstart.md * deepspeed_autotp_fastapi_quickstart.md * dify_quickstart.md * fastchat_quickstart.md * adjust tab style * fix link * fix link * add video preview * Small fixes * Small fix --------- Co-authored-by: Yuwen Hu <yuwen.hu@intel.com>
		
			
				
	
	
	
	
		
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bigdl-llm Migration Guide
This guide helps you migrate your bigdl-llm application to use ipex-llm.
Upgrade bigdl-llm package to ipex-llm
Note
This step assumes you have already installed
bigdl-llm.
You need to uninstall bigdl-llm and install ipex-llmWith your bigdl-llm conda environment activated, execute the following command according to your device type and location:
For CPU
pip uninstall -y bigdl-llm
pip install --pre --upgrade ipex-llm[all] # for cpu
For GPU
Choose either US or CN website for extra-index-url:
- 
For US:
pip uninstall -y bigdl-llm pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/ - 
For CN:
pip uninstall -y bigdl-llm pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/cn/ 
Migrate bigdl-llm code to ipex-llm
There are two options to migrate bigdl-llm code to ipex-llm.
1. Upgrade bigdl-llm code to ipex-llm
To upgrade bigdl-llm code to ipex-llm, simply replace all bigdl.llm with ipex_llm:
#from bigdl.llm.transformers import AutoModelForCausalLM # Original line
from ipex_llm.transformers import AutoModelForCausalLM #Updated line
model = AutoModelForCausalLM.from_pretrained(model_path,
                                             load_in_4bit=True,
                                             trust_remote_code=True)
2. Run bigdl-llm code in compatible mode (experimental)
To run in the compatible mode, simply add import ipex_llm at the beginning of the existing bigdl-llm code:
import ipex_llm # Add this line before any bigdl.llm imports
from bigdl.llm.transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained(model_path,
                                             load_in_4bit=True,
                                             trust_remote_code=True)