Instructions to use opencode/CodeLlama-7B-quotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use opencode/CodeLlama-7B-quotes with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "opencode/CodeLlama-7B-quotes") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from opencode/CodeLlama-7B-quotes: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/opencode/CodeLlama-7B-quotes/resolve/refs%2Fpr%2F1/adapter_model.bin
- Command line
-
hf download hf://opencode/CodeLlama-7B-quotes@refs/pr/1/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/opencode/CodeLlama-7B-quotes/resolve/refs%2Fpr%2F1/adapter_model.bin
134 MB
- Xet hash:
- d85357017a407084ed72711837b9dd7209e6474b853682ef628d786c2cad4bb0
- Size of remote file:
- 134 MB
- SHA256:
- 56e61fd63e094fb4c397d67f167a73aad748a7a82f8fad3466cd94fd1c52db5a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.