Instructions to use KpRT/combined-datset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KpRT/combined-datset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KpRT/combined-datset")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KpRT/combined-datset") model = AutoModelForTokenClassification.from_pretrained("KpRT/combined-datset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from KpRT/combined-datset: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/KpRT/combined-datset/resolve/main/tokenizer.json
- Command line
-
hf download hf://KpRT/combined-datset/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/KpRT/combined-datset/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.