Instructions to use jiosephlee/rejection_sampled_intern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiosephlee/rejection_sampled_intern with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jiosephlee/rejection_sampled_intern", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jiosephlee/rejection_sampled_intern", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
jiosephlee/sft_rejection_sampling_pgb_clin_herg_Intern-s1-mini-distill-dsv32-11k-samples_lr1e-05
a958d1b verified Download training_args.bin from jiosephlee/rejection_sampled_intern: direct link, hf CLI and curl.
- Browser
- Download file 6.74 kB
-
https://huggingface.co/jiosephlee/rejection_sampled_intern/resolve/main/training_args.bin
- Command line
-
hf download hf://jiosephlee/rejection_sampled_intern/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jiosephlee/rejection_sampled_intern/resolve/main/training_args.bin
6.74 kB
- Xet hash:
- cf1a91790bf58e6abf6e501b666cd3c091d0be0bf0846672f18bfdddf6d32c58
- Size of remote file:
- 6.74 kB
- SHA256:
- 181a1a8ea7fc8722a71d170e3a1b72b4fc9fe657322b05be89c0eb7a50f92a4c
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