Instructions to use pandalla/ChatLaw2E_plain_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pandalla/ChatLaw2E_plain_7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pandalla/ChatLaw2E_plain_7B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pandalla/ChatLaw2E_plain_7B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f14fc5de08b5dbfe333cb56e31ce7c522dae5c3e10aeba9a52603784cf34a73
- Size of remote file:
- 5.82 kB
- SHA256:
- 63c425463c796dad39baa93afb377f9bd439c5a82b7edce8505c86661e5472c1
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