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/training_args.bin from pruhtopia/bert-toc-classification: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/pruhtopia/bert-toc-classification/resolve/main/checkpoint-6000/training_args.bin
- Command line
-
hf download hf://pruhtopia/bert-toc-classification/checkpoint-6000/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pruhtopia/bert-toc-classification/resolve/main/checkpoint-6000/training_args.bin
4.73 kB
- Xet hash:
- d6ce4056067d909b2b60b32f712e1808ccbd52908dc035cf0693ac23315ce187
- Size of remote file:
- 4.73 kB
- SHA256:
- 6da5e30a3ef2a7c8718bce9ea0feed3aea75852257f56c9940fa20993d1343c2
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