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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/tokenizer.json from albertmartinez/bert-multilingual-sdg-classification: direct link, hf CLI and curl.
- Browser
- Download file 2.56 MB
-
https://huggingface.co/albertmartinez/bert-multilingual-sdg-classification/resolve/main/onnx/tokenizer.json
- Command line
-
hf download hf://albertmartinez/bert-multilingual-sdg-classification/onnx/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/albertmartinez/bert-multilingual-sdg-classification/resolve/main/onnx/tokenizer.json
2.56 MB
File too large to display, you can check the raw version instead.