Instructions to use m0kr4n3/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use m0kr4n3/checkpoints with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoderbase-1b") model = PeftModel.from_pretrained(base_model, "m0kr4n3/checkpoints") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from m0kr4n3/checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/m0kr4n3/checkpoints/resolve/main/training_args.bin
- Command line
-
hf download hf://m0kr4n3/checkpoints/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/m0kr4n3/checkpoints/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 5a38129579c72e19e35a53d2b353d45f9060c902de150584f7d854f6f5ab1f02
- Size of remote file:
- 4.92 kB
- SHA256:
- d212ccefd3727e7456adc8a83109f8602f982673c7aa00cbc761845aab92ee64
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