Text Classification
Transformers
ONNX
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use albertmartinez/bert-sdg-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertmartinez/bert-sdg-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="albertmartinez/bert-sdg-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("albertmartinez/bert-sdg-classification") model = AutoModelForSequenceClassification.from_pretrained("albertmartinez/bert-sdg-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 549fcb1599593878b4cc457620efac7aeeb04e7a75c854049c10103af23cae53
- Size of remote file:
- 438 MB
- SHA256:
- cf4b23623628b10e56df50ca239220b66f5aa38b7f71406bfd81717040b214ae
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