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:
# 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
Added TF and PT models
Browse files- flax_model.msgpack +3 -0
- generation_config.json +7 -0
- pytorch_model.bin +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:5b65da54660434a6c90896439edf0e251a7fbd31b5f60047a36531032693759e
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size 287515687
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generation_config.json
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{
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"_from_model_config": true,
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"decoder_start_token_id": 0,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.33.2"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:05682851bb04f787234186b38bff15ae1a50240da9a2a917da2e04139dcf504e
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size 287570309
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