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:
- 2105754267bad4b11645dd3725c78efd080c64159ac2c4e7b9fc917f8a569eea
- Size of remote file:
- 13.1 MB
- SHA256:
- 50923db586cdf72091d0237413229c1ab462ad2663040e987295d9e248044a8b
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