Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Maaz911/bert-intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maaz911/bert-intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Maaz911/bert-intent-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Maaz911/bert-intent-classifier") model = AutoModelForSequenceClassification.from_pretrained("Maaz911/bert-intent-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ec2a4a77fb2a4488498ba51c5f5979ae7b79feaaf8760ebb86ce334c7cd3dbb
- Size of remote file:
- 5.11 kB
- SHA256:
- 70c8edfbdca06cfdf3f99677f66b086a4373547e38961782d5a9931c1a141fc1
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