Instructions to use JulianPJ/BERT_T5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JulianPJ/BERT_T5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JulianPJ/BERT_T5") model = AutoModelForSeq2SeqLM.from_pretrained("JulianPJ/BERT_T5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from JulianPJ/BERT_T5: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/JulianPJ/BERT_T5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JulianPJ/BERT_T5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JulianPJ/BERT_T5/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- ec470af9164fa24c522d60fdcdb2288b0fafd6fbc4a982a989328fadd5aaf848
- Size of remote file:
- 242 MB
- SHA256:
- e5c4d6c4b515fd7cb63987ec78dbf86d87cc1553a9f80bf18b69adb44462c874
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