Instructions to use manueldeprada/t5-cord19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manueldeprada/t5-cord19 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("manueldeprada/t5-cord19") model = AutoModelForSeq2SeqLM.from_pretrained("manueldeprada/t5-cord19", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from manueldeprada/t5-cord19: direct link, hf CLI and curl.
- Browser
- Download file 427 Bytes
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https://huggingface.co/manueldeprada/t5-cord19/resolve/main/README.md
- Command line
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hf download hf://manueldeprada/t5-cord19/README.md
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curl -L -o README.md https://huggingface.co/manueldeprada/t5-cord19/resolve/main/README.md
427 Bytes
T5-base pretrained on CORD-19 dataset
The model has been pretrained on text and abstracts from the CORD-19 dataset, using a manually implemented denoising objetive similar to the original T5 denoising objective.
Model needs to be finetuned on downstream tasks.
Code avaliable in github: https://github.com/manueldeprada/Pretraining-T5-PyTorch-Lightning.