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moralclip-base
anaaa2/moralclip-base
moralclip-base is a zero-shot image classification model from anaaa2. Use it for the zero-shot image classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
MoralCLIP extends CLIP with explicit moral grounding based on Moral Foundations Theory (MFT). This model aligns image and text representations by shared moral meaning rather than purely semantic similarity.
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At a glance
- Task
- Zero-Shot Image Classification
- Library
- transformers
- License
- mit
- Model type
- clip
- Access
- Public
- Created
- Sep 10, 2025
- Updated
- Dec 23, 2025
- SHA
- 1e337922
Base models
Model card
From the Hugging Face model README
MoralCLIP
MoralCLIP extends CLIP with explicit moral grounding based on Moral Foundations Theory (MFT). This model aligns image and text representations by shared moral meaning rather than purely semantic similarity.
Model Details
- Base Model: openai/clip-vit-base-patch16
- Training Data: ~15k image-text pairs with MFT annotations
- Moral Foundations: Care, Fairness, Loyalty, Authority, Sanctity
- Paper: Under review
Usage
from transformers import CLIPModel, CLIPProcessor
from PIL import Image
import torch
model = CLIPModel.from_pretrained("anaaa2/moralclip-base")
processor = CLIPProcessor.from_pretrained("anaaa2/moralclip-base")
img = Image.open("image_path").convert("RGB")
inputs = processor(text=["a photo of care"], images=image, return_tensors="pt", padding=True)
outputs = model(**inputs)
image_embeds = outputs.image_embeds
text_embeds = outputs.text_embeds
- Task
- Zero-Shot Image Classification
- Library
- transformers
- Type
- clip
- License
- mit
- Languages
- en
- Created
- Sep 10, 2025
- Updated
- Dec 23, 2025