Instructions to use maksf8486/c2fb190c-1d1f-432e-88cb-3b31caf94fba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use maksf8486/c2fb190c-1d1f-432e-88cb-3b31caf94fba 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, "maksf8486/c2fb190c-1d1f-432e-88cb-3b31caf94fba") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f075ed97b698cd02f3737dea8d87c35eb8a7324401cf1ae8045b1a2847a4f72
- Size of remote file:
- 6.78 kB
- SHA256:
- 778f9cd70838ea8cd2d48cbed2ce152486a8571459fc4c37005045b0535477a1
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