Instructions to use RioJune/AG-KD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RioJune/AG-KD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="RioJune/AG-KD", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("RioJune/AG-KD", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("RioJune/AG-KD", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from RioJune/AG-KD: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/RioJune/AG-KD/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://RioJune/AG-KD@refs/pr/2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/RioJune/AG-KD/resolve/refs%2Fpr%2F2/tokenizer.json
1.36 MB
File too large to display, you can check the raw version instead.