Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
nlu
intent-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use cartesinus/multilingual_minilm-amazon-massive-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cartesinus/multilingual_minilm-amazon-massive-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cartesinus/multilingual_minilm-amazon-massive-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/multilingual_minilm-amazon-massive-intent") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/multilingual_minilm-amazon-massive-intent") - Notebooks
- Google Colab
- Kaggle
Commit ·
a90588a
1
Parent(s): f181731
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (ed4cca54a9869bcc83ccddf7e91517d63c91f7e2)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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