Instructions to use TomPanda/LLM-Restate-Discllaw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TomPanda/LLM-Restate-Discllaw with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/data/oss_bucket_0/mushuang/disc/") model = PeftModel.from_pretrained(base_model, "TomPanda/LLM-Restate-Discllaw") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d73b9c5dc4a9e6ad3d2817a5d787c4bc5939fcfc40038d0cf498148b0b94e234
- Size of remote file:
- 1.14 MB
- SHA256:
- f7d1ab69d25c74644af5c5e4dcd1cc6e96d33783dbd257b6bdea55b643c72813
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