Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Mukalingam0813/multilingual-Distilbert-intent-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mukalingam0813/multilingual-Distilbert-intent-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mukalingam0813/multilingual-Distilbert-intent-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mukalingam0813/multilingual-Distilbert-intent-classification") model = AutoModelForSequenceClassification.from_pretrained("Mukalingam0813/multilingual-Distilbert-intent-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03e55e6dcf9fe48764f8c09f4573bd3ffb3e15c7c66c6254f6ed27205928ac2d
- Size of remote file:
- 4.79 kB
- SHA256:
- d6f5b4c7772dc1bce284a22a38ea5ed2c44c13b3bed11d7e2ecafd296d993ca2
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