Transformers
PyTorch
JAX
English
t5
text2text-generation
biomedical
clinical
ul2
encoder-decoder
pretraining
medical
text-generation-inference
Instructions to use Siddharth63/pubmedul2-mini-nl8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siddharth63/pubmedul2-mini-nl8 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Siddharth63/pubmedul2-mini-nl8") model = AutoModelForSeq2SeqLM.from_pretrained("Siddharth63/pubmedul2-mini-nl8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Siddharth63/pubmedul2-mini-nl8: direct link, hf CLI and curl.
- Browser
- Download file 288 MB
-
https://huggingface.co/Siddharth63/pubmedul2-mini-nl8/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Siddharth63/pubmedul2-mini-nl8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Siddharth63/pubmedul2-mini-nl8/resolve/main/pytorch_model.bin
288 MB
- Xet hash:
- 8ab37b6a50b0c6d317c5c7ffe018f59aa5398f0120e51b6258fbffe9b2ba06ef
- Size of remote file:
- 288 MB
- SHA256:
- 05682851bb04f787234186b38bff15ae1a50240da9a2a917da2e04139dcf504e
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