Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use jonas/bert-base-uncased-finetuned-sdg-Mar23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonas/bert-base-uncased-finetuned-sdg-Mar23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jonas/bert-base-uncased-finetuned-sdg-Mar23")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jonas/bert-base-uncased-finetuned-sdg-Mar23") model = AutoModelForSequenceClassification.from_pretrained("jonas/bert-base-uncased-finetuned-sdg-Mar23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jonas/bert-base-uncased-finetuned-sdg-Mar23: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
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https://huggingface.co/jonas/bert-base-uncased-finetuned-sdg-Mar23/resolve/main/tokenizer.json
- Command line
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hf download hf://jonas/bert-base-uncased-finetuned-sdg-Mar23/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/jonas/bert-base-uncased-finetuned-sdg-Mar23/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.