Instructions to use mkychsu/semiconductor_graph_preflexor_grpo_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkychsu/semiconductor_graph_preflexor_grpo_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mkychsu/semiconductor_graph_preflexor_grpo_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mkychsu/semiconductor_graph_preflexor_grpo_2: direct link, hf CLI and curl.
- Browser
- Download file 7.1 kB
-
https://huggingface.co/mkychsu/semiconductor_graph_preflexor_grpo_2/resolve/main/training_args.bin
- Command line
-
hf download hf://mkychsu/semiconductor_graph_preflexor_grpo_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mkychsu/semiconductor_graph_preflexor_grpo_2/resolve/main/training_args.bin
7.1 kB
- Xet hash:
- 2bb05fec6100743ac89b7062782ef244f027b833a03857143a97aadac6b2c54d
- Size of remote file:
- 7.1 kB
- SHA256:
- 4eea4ce611162ce743290cf9ca096e9d3e0def76ada39dcc04c236ad074fb6c8
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