Image Classification
Transformers
Safetensors
PyTorch
English
qwen3_5
image-text-to-text
text-generation-inference
qwen3.8-27B
VisionGuardrail
evo-2.0
JSON
content-safety
content-moderation
multimodal
safety-classifier
guardrail
visual-safety
multimodal-content-filter
uncensored
mmcf
Instructions to use prithivMLmods/VisionGuardrail-Evo2-27B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/VisionGuardrail-Evo2-27B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/VisionGuardrail-Evo2-27B") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("prithivMLmods/VisionGuardrail-Evo2-27B") model = AutoModelForMultimodalLM.from_pretrained("prithivMLmods/VisionGuardrail-Evo2-27B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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base_model:
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pipeline_tag: image-
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datasets:
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base_model:
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pipeline_tag: image-classification
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datasets:
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