Instructions to use tannonk/bart_mini-SI_bart5_25-s1984 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tannonk/bart_mini-SI_bart5_25-s1984 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tannonk/bart_mini-SI_bart5_25-s1984") model = AutoModelForSeq2SeqLM.from_pretrained("tannonk/bart_mini-SI_bart5_25-s1984", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tannonk/bart_mini-SI_bart5_25-s1984: direct link, hf CLI and curl.
- Browser
- Download file 4.11 MB
-
https://huggingface.co/tannonk/bart_mini-SI_bart5_25-s1984/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tannonk/bart_mini-SI_bart5_25-s1984/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tannonk/bart_mini-SI_bart5_25-s1984/resolve/main/pytorch_model.bin
4.11 MB
- Xet hash:
- 2c7fbb64f1463be9d9a2ed4f4e1daf4bf81660ee71f85da3cfded94adf7660d1
- Size of remote file:
- 4.11 MB
- SHA256:
- b590c33d4610c6b0b5a5978be9166c3847cc67bb706213442b620a95f6c1ee1a
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