Instructions to use nbninh/57692212-0d5c-4e91-b2bd-42a4b4647a7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nbninh/57692212-0d5c-4e91-b2bd-42a4b4647a7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "nbninh/57692212-0d5c-4e91-b2bd-42a4b4647a7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6da3b9b05d387732238c2aefad49625f938ebf37d0d53ebccfd2d29438ba890
- Size of remote file:
- 83.9 MB
- SHA256:
- 5f98ad88a522d3a8bccd23c9a4323a3b8e7c48bdd251a8ea0486482b64c7e19e
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