Any-to-Any
Transformers
Safetensors
gemma4
image-text-to-text
gemma
google
paroquant
4-bit precision
Instructions to use Jeethu/gemma-4-E4B-it-PARO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeethu/gemma-4-E4B-it-PARO with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Jeethu/gemma-4-E4B-it-PARO") model = AutoModelForMultimodalLM.from_pretrained("Jeethu/gemma-4-E4B-it-PARO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6454ec93179260ad5fe6d6055cfd29132851a7bddd0ba29370827f4ca327d8e1
- Size of remote file:
- 10.1 GB
- SHA256:
- aebc474d5524488f56f7fa0382e3fcfe68f94a990bfdda7765deb9a3cdb9366f
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