Text Classification
Transformers
PyTorch
English
bert
sustainable-development-goals
SDG
social-impact
Instructions to use amannor/bert-base-uncased-sdg-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amannor/bert-base-uncased-sdg-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amannor/bert-base-uncased-sdg-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amannor/bert-base-uncased-sdg-classifier") model = AutoModelForSequenceClassification.from_pretrained("amannor/bert-base-uncased-sdg-classifier") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:70a1263cdbfa46daf74868a769d02478205cbc1446c89dd7ba04db27211d5494
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size 438012048
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