Instructions to use nblinh/9d94bc60-34ce-43f9-8b83-e855fe65505c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh/9d94bc60-34ce-43f9-8b83-e855fe65505c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/zephyr-sft") model = PeftModel.from_pretrained(base_model, "nblinh/9d94bc60-34ce-43f9-8b83-e855fe65505c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48d848e809499be13318285ffa19ef0def88b998733353774b9bdddc8509a730
- Size of remote file:
- 6.78 kB
- SHA256:
- 45538e3a232857059f47d606a5020956b7ee2cbd38c96bb4c9f729f7b0bef812
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