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