Instructions to use VARabi/ALDi-Token-DI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VARabi/ALDi-Token-DI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="VARabi/ALDi-Token-DI")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("VARabi/ALDi-Token-DI") model = AutoModelForTokenClassification.from_pretrained("VARabi/ALDi-Token-DI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from VARabi/ALDi-Token-DI: direct link, hf CLI and curl.
- Browser
- Download file 881 kB
-
https://huggingface.co/VARabi/ALDi-Token-DI/resolve/main/tokenizer.json
- Command line
-
hf download hf://VARabi/ALDi-Token-DI/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/VARabi/ALDi-Token-DI/resolve/main/tokenizer.json
881 kB
File too large to display, you can check the raw version instead.