Instructions to use Utkarsh524/codellama_utests_embedded_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Utkarsh524/codellama_utests_embedded_new 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_new") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-600/optimizer.pt from Utkarsh524/codellama_utests_embedded_new: direct link, hf CLI and curl.
- Browser
- Download file 537 MB
-
https://huggingface.co/Utkarsh524/codellama_utests_embedded_new/resolve/main/checkpoint-600/optimizer.pt
- Command line
-
hf download hf://Utkarsh524/codellama_utests_embedded_new/checkpoint-600/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Utkarsh524/codellama_utests_embedded_new/resolve/main/checkpoint-600/optimizer.pt
537 MB
- Xet hash:
- 3a7582ca88be307e8ae97c4b0c9bc2f261331ecafaee4f5506c721e0c78ffa51
- Size of remote file:
- 537 MB
- SHA256:
- 26ba801f36aa498c7bc76d0be675bce34ef81302b584f3708dc1cab837b41c4d
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