Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
deberta-v2
Generated from Trainer
nlu
intent-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use cartesinus/mdeberta-v3-base_amazon-massive_intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cartesinus/mdeberta-v3-base_amazon-massive_intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cartesinus/mdeberta-v3-base_amazon-massive_intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/mdeberta-v3-base_amazon-massive_intent") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/mdeberta-v3-base_amazon-massive_intent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7242e7e513f18d4078618d81b5f07cf5c8cb50be72f8116fdfe4871fd752604
- Size of remote file:
- 3.44 kB
- SHA256:
- 3de967f432567352fb688c1d52d45fc5944b598b033a5c49d24437ee9aedc713
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