Instructions to use akhilaaa3/Jev-Omni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akhilaaa3/Jev-Omni with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akhilaaa3/Jev-Omni")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("akhilaaa3/Jev-Omni") model = AutoModelForMultimodalLM.from_pretrained("akhilaaa3/Jev-Omni", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download assets/medium-calibration.svg from akhilaaa3/Jev-Omni: direct link, hf CLI and curl.
- Browser
- Download file 5.03 kB
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https://huggingface.co/akhilaaa3/Jev-Omni/resolve/main/assets/medium-calibration.svg
- Command line
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hf download hf://akhilaaa3/Jev-Omni/assets/medium-calibration.svg
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curl -L -o medium-calibration.svg https://huggingface.co/akhilaaa3/Jev-Omni/resolve/main/assets/medium-calibration.svg
5.03 kB