Instructions to use davanstrien/dataset-schema-task-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/dataset-schema-task-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/dataset-schema-task-classifier", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/dataset-schema-task-classifier", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("davanstrien/dataset-schema-task-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from davanstrien/dataset-schema-task-classifier: direct link, hf CLI and curl.
- Browser
- Download file 335 Bytes
-
https://huggingface.co/davanstrien/dataset-schema-task-classifier/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://davanstrien/dataset-schema-task-classifier/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/davanstrien/dataset-schema-task-classifier/resolve/main/tokenizer_config.json
335 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|startoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<|mask|>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|pad|>", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |