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
Download tokenizer.json from prithivMLmods/VisionGuardrail-Evo2-27B: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/prithivMLmods/VisionGuardrail-Evo2-27B/resolve/main/tokenizer.json
- Command line
-
hf download hf://prithivMLmods/VisionGuardrail-Evo2-27B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/prithivMLmods/VisionGuardrail-Evo2-27B/resolve/main/tokenizer.json
20 MB
- Xet hash:
- cc31271e547c3c57a48bb8e7f2328d24edbab578d20e8fb1b1329481929f13bd
- Size of remote file:
- 20 MB
- SHA256:
- 394a997fc1db2fd404ef14b59385a73f10f0164a92db69f87090cc658c9abc10
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