Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use gokuls/bert-uncased-massive-intent-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gokuls/bert-uncased-massive-intent-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gokuls/bert-uncased-massive-intent-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gokuls/bert-uncased-massive-intent-classification") model = AutoModelForSequenceClassification.from_pretrained("gokuls/bert-uncased-massive-intent-classification") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
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