Instructions to use Infernaught/codealpaca51295 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Infernaught/codealpaca51295 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "Infernaught/codealpaca51295") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from Infernaught/codealpaca51295: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/Infernaught/codealpaca51295/resolve/refs%2Fpr%2F1/adapter_model.bin
- Command line
-
hf download hf://Infernaught/codealpaca51295@refs/pr/1/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/Infernaught/codealpaca51295/resolve/refs%2Fpr%2F1/adapter_model.bin
16.8 MB
- Xet hash:
- 3eb3fd32698c9677a8104e5be976b7ef2b0d4e7c4ebb79b5e42837f8147e71c5
- Size of remote file:
- 16.8 MB
- SHA256:
- b21e4fe06a8be41542f3853603e95a7cb8730f47269a678eb3b80a492bcf6f30
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.