Instructions to use davanstrien/finepdfs-edu-purpose-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use davanstrien/finepdfs-edu-purpose-classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("davanstrien/finepdfs-edu-purpose-classifier") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
davanstrien HF Staff
Release selected document-purpose classifier and inference example
3055b70 verified Download tokenizer_config.json from davanstrien/finepdfs-edu-purpose-classifier: direct link, hf CLI and curl.
- Browser
- Download file 379 Bytes
-
https://huggingface.co/davanstrien/finepdfs-edu-purpose-classifier/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://davanstrien/finepdfs-edu-purpose-classifier/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/davanstrien/finepdfs-edu-purpose-classifier/resolve/main/tokenizer_config.json
379 Bytes
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 1024, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "[UNK]" | |
| } | |