Instructions to use cimol/7b62ba39-466c-4514-b884-70778220730f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/7b62ba39-466c-4514-b884-70778220730f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "cimol/7b62ba39-466c-4514-b884-70778220730f") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from cimol/7b62ba39-466c-4514-b884-70778220730f: direct link, hf CLI and curl.
- Browser
- Download file 646 MB
-
https://huggingface.co/cimol/7b62ba39-466c-4514-b884-70778220730f/resolve/main/adapter_model.bin
- Command line
-
hf download hf://cimol/7b62ba39-466c-4514-b884-70778220730f/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/cimol/7b62ba39-466c-4514-b884-70778220730f/resolve/main/adapter_model.bin
646 MB
- Xet hash:
- 7c21ef74684d67cc5a29b8cfa65fc69e1336b43f1514966249a61ade61e8b56b
- Size of remote file:
- 646 MB
- SHA256:
- d34d26f7697b91e8399c569869a9e646e67de9f2036b8f8e19adb6634f453e2b
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