Instructions to use pandalla/ChatLaw2-MoE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pandalla/ChatLaw2-MoE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pandalla/ChatLaw2-MoE", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pandalla/ChatLaw2-MoE", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from pandalla/ChatLaw2-MoE: direct link, hf CLI and curl.
- Browser
- Download file 132 Bytes
-
https://huggingface.co/pandalla/ChatLaw2-MoE/resolve/main/tokenizer.model
- Command line
-
hf download hf://pandalla/ChatLaw2-MoE/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/pandalla/ChatLaw2-MoE/resolve/main/tokenizer.model
132 Bytes
- Xet hash:
- 95603b05d82b72c1252d0f1633d29a44fb2206cc9d4acef3db7bc40e3a444645
- Size of remote file:
- 132 Bytes
- SHA256:
- 0657b9b7d5a442264c8be0d934dbaf363bfb55d03c29f92c1716684a62a275d8
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