Instructions to use diyanigam/CookBook with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use diyanigam/CookBook with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "diyanigam/CookBook") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from diyanigam/CookBook: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/diyanigam/CookBook/resolve/main/adapter_model.bin
- Command line
-
hf download hf://diyanigam/CookBook/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/diyanigam/CookBook/resolve/main/adapter_model.bin
134 MB
- Xet hash:
- 5f56fa3e71d19c7e861a567d4994ce854dbb0be0847a88214c0a97e038645ecc
- Size of remote file:
- 134 MB
- SHA256:
- 99708a6771acbe6d8edc5de1d26af13c5fa8955acae63e904525031d87009335
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