Text Classification
Transformers
Safetensors
gemma4_unified
image-text-to-text
multimodal
merged
decision-model
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
Add decision-model tag
#2
by mishig HF Staff - opened
Hi @akhilaaa3 ,
This PR adds the decision-model tag to the model card metadata, so Jev-Omni shows up next to the other decision models on the Hub: https://huggingface.co/models?other=decision-model
It's a one-line metadata change, nothing else in the card is touched.
Sure. Thanks.
akhilaaa3 changed pull request status to merged