Transformers
PyTorch
English
t5
text2text-generation
t5-small
natural language generation
conversational system
task-oriented dialog
Eval Results (legacy)
text-generation-inference
Instructions to use ConvLab/t5-small-nlg-multiwoz21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConvLab/t5-small-nlg-multiwoz21 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ConvLab/t5-small-nlg-multiwoz21") model = AutoModelForSeq2SeqLM.from_pretrained("ConvLab/t5-small-nlg-multiwoz21") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9eccc63a6b850fd66d054f009fb08d660ac46aceeee43f55a0475445daf8eb5
- Size of remote file:
- 242 MB
- SHA256:
- 5d940d94a07953f50e78fa662c7a786dd07d6fdb3ed283b4ab7550b71ce98627
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.