Instructions to use ArthurZ/d3-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArthurZ/d3-edge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="ArthurZ/d3-edge")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArthurZ/d3-edge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ArthurZ/d3-edge: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/ArthurZ/d3-edge/resolve/main/tokenizer.json
- Command line
-
hf download hf://ArthurZ/d3-edge/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ArthurZ/d3-edge/resolve/main/tokenizer.json
20 MB
- Xet hash:
- e558cdad9a88d177076f9525ed4ef2d55dfd5dafafd6baac7c6105590ab49b7b
- Size of remote file:
- 20 MB
- SHA256:
- a5cd9732badce41de57e6efce8302930ded1c1188c5f81feb2bd6c24c4a1941f
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