Instructions to use Utkarsh524/codellama_utests_embedded_v3_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Utkarsh524/codellama_utests_embedded_v3_full 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, "Utkarsh524/codellama_utests_embedded_v3_full") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-652/optimizer.pt from Utkarsh524/codellama_utests_embedded_v3_full: direct link, hf CLI and curl.
- Browser
- Download file 137 MB
-
https://huggingface.co/Utkarsh524/codellama_utests_embedded_v3_full/resolve/main/checkpoint-652/optimizer.pt
- Command line
-
hf download hf://Utkarsh524/codellama_utests_embedded_v3_full/checkpoint-652/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Utkarsh524/codellama_utests_embedded_v3_full/resolve/main/checkpoint-652/optimizer.pt
137 MB
- Xet hash:
- 94a083c725c7b7c5d6abed399ce04c0f3d10525d60c26fff31bc022cfe6f69c7
- Size of remote file:
- 137 MB
- SHA256:
- 959749e8edb30eac1731a6896ed1187bd7ce4ecdaa58af2395702924a9be3e8f
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