Instructions to use dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040 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, "dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040: direct link, hf CLI and curl.
- Browser
- Download file 70.5 MB
-
https://huggingface.co/dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dada22231/d6f45fc9-70fb-45e0-9a7f-0ee2b7506040/resolve/main/adapter_model.bin
70.5 MB
- Xet hash:
- 4a8ff4babb8533c4f83ba95f7247af34158f3b15b9e5b2bdcd3f6492ba64dc75
- Size of remote file:
- 70.5 MB
- SHA256:
- c69aa30f682bfc3ea2b882fa6d573f81d84d2f8ab505609bcba03d5387b22421
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