Instructions to use thaffggg/a4c6e736-e9a9-45a7-8568-0843fbfe65d2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thaffggg/a4c6e736-e9a9-45a7-8568-0843fbfe65d2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4") model = PeftModel.from_pretrained(base_model, "thaffggg/a4c6e736-e9a9-45a7-8568-0843fbfe65d2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c386f0a79fbedc654b8135b9e59bea8e47c798fa7fca493030ad1cec10a6442
- Size of remote file:
- 83.9 MB
- SHA256:
- b68cb97e8a27a372c896433f53cd0bead0cce2420af9aaabf2457c605ccc6011
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