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 model.safetensors from VARabi/ALDi-Token-DI: direct link, hf CLI and curl.
- Browser
- Download file 649 MB
-
https://huggingface.co/VARabi/ALDi-Token-DI/resolve/main/model.safetensors
- Command line
-
hf download hf://VARabi/ALDi-Token-DI/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/VARabi/ALDi-Token-DI/resolve/main/model.safetensors
649 MB
- Xet hash:
- 9fb9359b043b6b39c7e677c56b34b5aae7278999d639fa962ea8655f1da70d41
- Size of remote file:
- 649 MB
- SHA256:
- 926230da6778ab9c992c75e467e48e0974da21f089e1f63ca20f02dd34005dca
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