Instructions to use amcoff/classify_skolmat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amcoff/classify_skolmat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amcoff/classify_skolmat")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amcoff/classify_skolmat") model = AutoModelForSequenceClassification.from_pretrained("amcoff/classify_skolmat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from amcoff/classify_skolmat: direct link, hf CLI and curl.
- Browser
- Download file 152 Bytes
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https://huggingface.co/amcoff/classify_skolmat/resolve/main/.gitattributes
- Command line
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hf download hf://amcoff/classify_skolmat/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/amcoff/classify_skolmat/resolve/main/.gitattributes
152 Bytes
| model.onnx filter=lfs diff=lfs merge=lfs -text | |
| tokenizer.json filter=lfs diff=lfs merge=lfs -text | |
| pytorch_model.bin filter=lfs diff=lfs merge=lfs -text | |