Instructions to use VARabi/ALDi-Token-DI-30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VARabi/ALDi-Token-DI-30 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="VARabi/ALDi-Token-DI-30")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("VARabi/ALDi-Token-DI-30") model = AutoModelForTokenClassification.from_pretrained("VARabi/ALDi-Token-DI-30", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (4d1717254f93c9dc13c9f2f319ab11acc37c4bb1)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ea230046cd288ca903ba5a5f1402ffc23ad03b5776225edd7950f5cde4c43c16
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size 649049008
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