Instructions to use kimbk/test_bart_r3f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kimbk/test_bart_r3f with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kimbk/test_bart_r3f") model = AutoModelForSeq2SeqLM.from_pretrained("kimbk/test_bart_r3f", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kimbk/test_bart_r3f: direct link, hf CLI and curl.
- Browser
- Download file 187 MB
-
https://huggingface.co/kimbk/test_bart_r3f/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kimbk/test_bart_r3f/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kimbk/test_bart_r3f/resolve/main/pytorch_model.bin
187 MB
- Xet hash:
- 27bbd230e0ef44cd72971a1997075b75fe8bf350a9ed8eead8b9dfabdf2102f1
- Size of remote file:
- 187 MB
- SHA256:
- 498032165e972aec5e46185b11fe0ecccf94a1ab328f010af76c44bf09b51dab
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