Transformers
PyTorch
English
t5
text2text-generation
scientific names
text generation
text-generation-inference
Instructions to use rosamondthalken/t5-base-sci-names with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rosamondthalken/t5-base-sci-names with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rosamondthalken/t5-base-sci-names") model = AutoModelForSeq2SeqLM.from_pretrained("rosamondthalken/t5-base-sci-names", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6470b84a2b1cbdb4edc42e48948d72c1ccbfbc4aa9e870883655cf0658e3d114
- Size of remote file:
- 892 MB
- SHA256:
- c762fdfccfcacb7ce27f2963a71aed84e23532efed3a5eb2da4e93b8659c32d9
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