Image Classification
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Instructions to use OpenDILabCommunity/HUMOR-RM-Keye-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenDILabCommunity/HUMOR-RM-Keye-VL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OpenDILabCommunity/HUMOR-RM-Keye-VL") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenDILabCommunity/HUMOR-RM-Keye-VL", dtype="auto") - Notebooks
- Google Colab
- Kaggle
karroyan commited on
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Parent(s): a28a72c
doc(lxy): add example figure to readme
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README.md
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self.template = get_template_and_fix_tokenizer(self.tokenizer, data_args)
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# 2. Load Base Model
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print("Loading Keye-VL Base...")
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self.model = AutoModel.from_pretrained(
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4. **Detailed Boring:** Subtle text changes that kill the joke.
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5. **Generated:** Fine-grained comparison between model-generated memes.
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## Citation
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```bibtex
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self.template = get_template_and_fix_tokenizer(self.tokenizer, data_args)
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# 2. Load Base Model
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self.model = AutoModel.from_pretrained(
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model_args.model_name_or_path,
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trust_remote_code=True,
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4. **Detailed Boring:** Subtle text changes that kill the joke.
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5. **Generated:** Fine-grained comparison between model-generated memes.
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## Citation
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```bibtex
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assets/datasets_with_different_tier.png
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