Text Classification
Transformers
ONNX
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use albertmartinez/bert-multilingual-sdg-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertmartinez/bert-multilingual-sdg-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="albertmartinez/bert-multilingual-sdg-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("albertmartinez/bert-multilingual-sdg-classification") model = AutoModelForSequenceClassification.from_pretrained("albertmartinez/bert-multilingual-sdg-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7abb8b64c9b8ba0237f5cfe1772dd3586aa5083780d4a3eca9ea318fb514d673
- Size of remote file:
- 5.43 kB
- SHA256:
- 10302ae0a50fe93097fcf3f7ab9b99aa2ba272d672f07f8ec0b031bc937df990
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