Transformers
PyTorch
JAX
English
t5
text2text-generation
biomedical
clinical
ul2
encoder-decoder
pretraining
medical
text-generation-inference
Instructions to use Siddharth63/pubmedul2_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siddharth63/pubmedul2_small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Siddharth63/pubmedul2_small") model = AutoModelForSeq2SeqLM.from_pretrained("Siddharth63/pubmedul2_small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Siddharth63/pubmedul2_small: direct link, hf CLI and curl.
- Browser
- Download file 308 MB
-
https://huggingface.co/Siddharth63/pubmedul2_small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Siddharth63/pubmedul2_small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Siddharth63/pubmedul2_small/resolve/main/pytorch_model.bin
308 MB
- Xet hash:
- 6e262d725101b62b9d2132567e5a2585bf3bdb47949ae4eb366894983e69e5aa
- Size of remote file:
- 308 MB
- SHA256:
- 12a7fce4133dcd5246af47244a9cc92a1788a4d88de985e15f418b59c739c6c6
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