Text Classification
Transformers
ONNX
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use albertmartinez/distilbert-multilingual-sdg-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertmartinez/distilbert-multilingual-sdg-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="albertmartinez/distilbert-multilingual-sdg-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("albertmartinez/distilbert-multilingual-sdg-classification") model = AutoModelForSequenceClassification.from_pretrained("albertmartinez/distilbert-multilingual-sdg-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a1c44e2a61e4f4455954b448113b8399892dd26a7ec1d770c8f88cfc77df327
- Size of remote file:
- 541 MB
- SHA256:
- 7010d2d9ff3876817ee4559d03ddd0fdd01e4154cb7e466af3b3d9a5ca22d952
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