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-tm1-context3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConvLab/t5-small-nlu-tm1-context3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ConvLab/t5-small-nlu-tm1-context3") model = AutoModelForSeq2SeqLM.from_pretrained("ConvLab/t5-small-nlu-tm1-context3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 785a1830ae0af7e2b9698820d5f3137b033f2740e505b212e1cae3fb121414e8
- Size of remote file:
- 242 MB
- SHA256:
- a22cc20907597853170013e3a2e036eac43afefa2eb8d328fed2e7dee0dcdac6
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