Instructions to use aleegis10/cd899803-f2b7-46da-b991-1e77ebf812fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis10/cd899803-f2b7-46da-b991-1e77ebf812fa 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, "aleegis10/cd899803-f2b7-46da-b991-1e77ebf812fa") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aleegis10/cd899803-f2b7-46da-b991-1e77ebf812fa: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/aleegis10/cd899803-f2b7-46da-b991-1e77ebf812fa/resolve/main/training_args.bin
- Command line
-
hf download hf://aleegis10/cd899803-f2b7-46da-b991-1e77ebf812fa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aleegis10/cd899803-f2b7-46da-b991-1e77ebf812fa/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 54731ac167292e57f9f7b8348554f6a062b870e54d8054f640dc5eea99081b21
- Size of remote file:
- 6.84 kB
- SHA256:
- 7ca8ef3de05ce12ecf47a9e8a02d6dd0c6c76bed5f2b6948c219be2e4be31fbf
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