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 checkpoint-6000/optimizer.pt from pruhtopia/bert-toc-classification: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/pruhtopia/bert-toc-classification/resolve/main/checkpoint-6000/optimizer.pt
- Command line
-
hf download hf://pruhtopia/bert-toc-classification/checkpoint-6000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/pruhtopia/bert-toc-classification/resolve/main/checkpoint-6000/optimizer.pt
876 MB
- Xet hash:
- 5125d6852064c1b196c0ba31aa2d5b160eb260c3dd3a578d5d254ac3cacabedb
- Size of remote file:
- 876 MB
- SHA256:
- 4311cfc2d6326c7ccfda52d87d2b2ce9c9cdbd96a9feb65ec87a2c9003c84697
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