Instructions to use demohong/7e98e653-74a4-4e80-a40f-d0da8f46d88c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use demohong/7e98e653-74a4-4e80-a40f-d0da8f46d88c 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, "demohong/7e98e653-74a4-4e80-a40f-d0da8f46d88c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d8e7027dc037ca84082a9354d01722557de66f2535d0ebbee159d7a410e9d75
- Size of remote file:
- 84 MB
- SHA256:
- adf5db003cec6d010377489ecbc3e4188bfca7c8358b95a6ea8dd773d6f26ba9
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