Transformers
PyTorch
English
t5
text2text-generation
t5-small
natural language understanding
conversational system
task-oriented dialog
Eval Results (legacy)
text-generation-inference
Instructions to use ConvLab/t5-small-nlu-sgd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConvLab/t5-small-nlu-sgd with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ConvLab/t5-small-nlu-sgd") model = AutoModelForSeq2SeqLM.from_pretrained("ConvLab/t5-small-nlu-sgd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4941548d8383bc7b0962fefe6e2ab4d2a42509cc2e224220159fa8e52b53f748
- Size of remote file:
- 242 MB
- SHA256:
- ad1ded8fab34581721c53f93b21c2f57fc76418d302999ba19e50bf3d6242a28
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