Instructions to use romainnn/2da3d576-a2e0-43ca-ab56-ba6262085721 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use romainnn/2da3d576-a2e0-43ca-ab56-ba6262085721 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jhflow/mistral7b-lora-multi-turn-v2") model = PeftModel.from_pretrained(base_model, "romainnn/2da3d576-a2e0-43ca-ab56-ba6262085721") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/tokenizer.json from romainnn/2da3d576-a2e0-43ca-ab56-ba6262085721: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
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https://huggingface.co/romainnn/2da3d576-a2e0-43ca-ab56-ba6262085721/resolve/201bc893c827063daf6e9593b1250c938f8a2d21/last-checkpoint/tokenizer.json
- Command line
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hf download hf://romainnn/2da3d576-a2e0-43ca-ab56-ba6262085721@201bc893c827063daf6e9593b1250c938f8a2d21/last-checkpoint/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/romainnn/2da3d576-a2e0-43ca-ab56-ba6262085721/resolve/201bc893c827063daf6e9593b1250c938f8a2d21/last-checkpoint/tokenizer.json
3.51 MB
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