Instructions to use vensonaa/venkat-codellama-7b-Java-finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vensonaa/venkat-codellama-7b-Java-finetuning 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, "vensonaa/venkat-codellama-7b-Java-finetuning") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from vensonaa/venkat-codellama-7b-Java-finetuning: direct link, hf CLI and curl.
- Browser
- Download file 8.43 MB
-
https://huggingface.co/vensonaa/venkat-codellama-7b-Java-finetuning/resolve/main/adapter_model.bin
- Command line
-
hf download hf://vensonaa/venkat-codellama-7b-Java-finetuning/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/vensonaa/venkat-codellama-7b-Java-finetuning/resolve/main/adapter_model.bin
8.43 MB
- Xet hash:
- a2d275c708c21b3baf75324ffdbbb8cf039547aa105b201cc639b2d0baea9a8f
- Size of remote file:
- 8.43 MB
- SHA256:
- b16606299362827773c0a4eb09a8fc3816ae862788a8b1d7ac8ecb0b12832388
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