Instructions to use cimol/51d7c703-1b14-4d1f-9f35-7304034c10bf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/51d7c703-1b14-4d1f-9f35-7304034c10bf with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "cimol/51d7c703-1b14-4d1f-9f35-7304034c10bf") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from cimol/51d7c703-1b14-4d1f-9f35-7304034c10bf: direct link, hf CLI and curl.
- Browser
- Download file 646 MB
-
https://huggingface.co/cimol/51d7c703-1b14-4d1f-9f35-7304034c10bf/resolve/main/adapter_model.bin
- Command line
-
hf download hf://cimol/51d7c703-1b14-4d1f-9f35-7304034c10bf/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/cimol/51d7c703-1b14-4d1f-9f35-7304034c10bf/resolve/main/adapter_model.bin
646 MB
- Xet hash:
- bab6284872d2013b40f2d240bd1ecdbfa70d3f2238cebd8bee04db4d3b85cac7
- Size of remote file:
- 646 MB
- SHA256:
- f4a6e7be61f7f4b9992c8e53f54c4caa622e1bbb0fceb4547155b294cec350ea
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