Instructions to use linhtran92/intentdetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linhtran92/intentdetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="linhtran92/intentdetection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("linhtran92/intentdetection") model = AutoModelForSequenceClassification.from_pretrained("linhtran92/intentdetection") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5d94c0d4207495b966d1fab5e0cfedb0df29f75a44fa586a79c73bffd93d7134
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size 437961724
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