Instructions to use Serega6678/tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Serega6678/tmp with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "Serega6678/tmp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06fa99e5d68912845d236cb3b6d2f052c001575639054e2dead46a18a5a5edad
- Size of remote file:
- 16.8 MB
- SHA256:
- 52c038acdf4f04ada424a48b4442868db8539473c8c209cbfe06568c76a52bc3
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