Instructions to use prxy5608/a916cb1e-8c66-47a9-9f45-1af6967ec012 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/a916cb1e-8c66-47a9-9f45-1af6967ec012 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, "prxy5608/a916cb1e-8c66-47a9-9f45-1af6967ec012") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b9c6a52ab26041158bb67aaecf483e624c78a44c3748f03a7bcb00ac08bea2d
- Size of remote file:
- 671 MB
- SHA256:
- 4269a001c1f051e2dc07b78baeb5b2f667858e6b89dee8a5b6d556c68f49fb6c
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