Transformers
PyTorch
JAX
English
t5
text2text-generation
biomedical
clinical
ul2
encoder-decoder
pretraining
medical
text-generation-inference
Instructions to use Siddharth63/pubmedul2-tiny-nl6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siddharth63/pubmedul2-tiny-nl6 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Siddharth63/pubmedul2-tiny-nl6") model = AutoModelForSeq2SeqLM.from_pretrained("Siddharth63/pubmedul2-tiny-nl6") - Notebooks
- Google Colab
- Kaggle
Commit ·
d0287d4
1
Parent(s): a220878
Update ul2_tasks.py
Browse files- ul2_tasks.py +1 -1
ul2_tasks.py
CHANGED
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@@ -26,7 +26,7 @@ S_DENOISER_TOKEN_PREFIX = "[S2S]"
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TaskRegistry = seqio.TaskRegistry
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vocabulary = seqio.SentencePieceVocabulary('spiece.model'
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DEFAULT_OUTPUT_FEATURES = {
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"inputs": seqio.Feature(vocabulary=vocabulary, add_eos=True, required=False),
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TaskRegistry = seqio.TaskRegistry
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vocabulary = seqio.SentencePieceVocabulary('spiece.model')
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DEFAULT_OUTPUT_FEATURES = {
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"inputs": seqio.Feature(vocabulary=vocabulary, add_eos=True, required=False),
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