Instructions to use cilooor/08d69553-cdcd-450a-bad2-a81b3c3c8fe7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cilooor/08d69553-cdcd-450a-bad2-a81b3c3c8fe7 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "cilooor/08d69553-cdcd-450a-bad2-a81b3c3c8fe7") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from cilooor/08d69553-cdcd-450a-bad2-a81b3c3c8fe7: direct link, hf CLI and curl.
- Browser
- Download file 141 MB
-
https://huggingface.co/cilooor/08d69553-cdcd-450a-bad2-a81b3c3c8fe7/resolve/main/adapter_model.bin
- Command line
-
hf download hf://cilooor/08d69553-cdcd-450a-bad2-a81b3c3c8fe7/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/cilooor/08d69553-cdcd-450a-bad2-a81b3c3c8fe7/resolve/main/adapter_model.bin
141 MB
- Xet hash:
- ce154ce0d219ae349609e01ff523dc42fe2bb7758d1af506941c73a9c7574b15
- Size of remote file:
- 141 MB
- SHA256:
- 387400c1ced8486484ebd5798f9ae97b056f0e67036c5cef4dfd4583551a2b7b
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