Instructions to use pruhtopia/bert-toc-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pruhtopia/bert-toc-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pruhtopia/bert-toc-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pruhtopia/bert-toc-classification") model = AutoModelForSequenceClassification.from_pretrained("pruhtopia/bert-toc-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from pruhtopia/bert-toc-classification: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/pruhtopia/bert-toc-classification/resolve/main/model.safetensors
- Command line
-
hf download hf://pruhtopia/bert-toc-classification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/pruhtopia/bert-toc-classification/resolve/main/model.safetensors
438 MB
- Xet hash:
- 1f895ad885e7a7c49b10a521bc61785be91bd1ad11d2d51214ba3713ef1249ce
- Size of remote file:
- 438 MB
- SHA256:
- 1d817e81efc74d4b7fc1dcfd07d035502ffc6996789aa45ffd45bcb67e0af4eb
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