Instructions to use thakkkkkk/ffdd36c7-b752-465c-92ff-502c174b0c53 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thakkkkkk/ffdd36c7-b752-465c-92ff-502c174b0c53 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Math-7B-Instruct") model = PeftModel.from_pretrained(base_model, "thakkkkkk/ffdd36c7-b752-465c-92ff-502c174b0c53") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from thakkkkkk/ffdd36c7-b752-465c-92ff-502c174b0c53: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/thakkkkkk/ffdd36c7-b752-465c-92ff-502c174b0c53/resolve/main/training_args.bin
- Command line
-
hf download hf://thakkkkkk/ffdd36c7-b752-465c-92ff-502c174b0c53/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thakkkkkk/ffdd36c7-b752-465c-92ff-502c174b0c53/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- cae0d59100aad8f7dd1e1f93b13e643114526dd2775e007054decc7ce9badd4b
- Size of remote file:
- 6.78 kB
- SHA256:
- 995cb183435d584f8182651e6b7ae4ae0a3380fb1bc8931e3c6537fb75292354
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