Instructions to use bane5631/51433eb1-948d-44e3-92aa-6d4ece29949c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/51433eb1-948d-44e3-92aa-6d4ece29949c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B") model = PeftModel.from_pretrained(base_model, "bane5631/51433eb1-948d-44e3-92aa-6d4ece29949c") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from bane5631/51433eb1-948d-44e3-92aa-6d4ece29949c: direct link, hf CLI and curl.
- Browser
- Download file 17.7 MB
-
https://huggingface.co/bane5631/51433eb1-948d-44e3-92aa-6d4ece29949c/resolve/main/adapter_model.bin
- Command line
-
hf download hf://bane5631/51433eb1-948d-44e3-92aa-6d4ece29949c/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/bane5631/51433eb1-948d-44e3-92aa-6d4ece29949c/resolve/main/adapter_model.bin
17.7 MB
- Xet hash:
- 8f0579abc0493016d8113a0802fbdc1188e71d56b9d1920bf07df35f5d744322
- Size of remote file:
- 17.7 MB
- SHA256:
- 03e0d5d8e5786c4297a2ab0bdb397e77d576a855ed773fab78f417ebebf4d802
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