Instructions to use wasantha285/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use wasantha285/results with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder2-7b") model = PeftModel.from_pretrained(base_model, "wasantha285/results") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wasantha285/results: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/wasantha285/results/resolve/main/training_args.bin
- Command line
-
hf download hf://wasantha285/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wasantha285/results/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 502ad1598e57eb7f455a6ce0b27375c3e1b3b7aa79682407a1c76402e19ea4f9
- Size of remote file:
- 5.3 kB
- SHA256:
- 5687cc5a83f342ee3d0b0c8879a4505d763b4ad03bfc98ba643c9f09a6b939c2
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