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
- Xet hash:
- de40bd6e6ccd44b3d4f8725f795bbc14e9c1d941feffd05c0fe8609157c7122b
- Size of remote file:
- 168 MB
- SHA256:
- 9eba72d8f33f1080e7d0c79d7b9a4d04bae5cba5f9225a6d194eec904d4f2e80
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