Instructions to use dzanbek/f23f2a9a-0d72-4c9d-85f8-5c9dfbfcb874 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/f23f2a9a-0d72-4c9d-85f8-5c9dfbfcb874 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "dzanbek/f23f2a9a-0d72-4c9d-85f8-5c9dfbfcb874") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from dzanbek/f23f2a9a-0d72-4c9d-85f8-5c9dfbfcb874: direct link, hf CLI and curl.
- Browser
- Download file 80 MB
-
https://huggingface.co/dzanbek/f23f2a9a-0d72-4c9d-85f8-5c9dfbfcb874/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://dzanbek/f23f2a9a-0d72-4c9d-85f8-5c9dfbfcb874/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/dzanbek/f23f2a9a-0d72-4c9d-85f8-5c9dfbfcb874/resolve/main/adapter_model.safetensors
80 MB
- Xet hash:
- a27b7b85744b6d3e27b69741b214bfbccd91ff3b7310c397989eb820153612a5
- Size of remote file:
- 80 MB
- SHA256:
- db87586bc7bb49254a6bc25bdcecb51e41905ce54d62e17d2d9ad15b48094712
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