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license: mit
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-------
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Love ❤️ this CLIP?
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</details>
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### 📊 Standard Benchmark Evaluation
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🌟 = This Model
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license: mit
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### Regression CLIP - with strong typographic robustness!
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- Fine-tuned using CLS-Patch Linear Regression teachers
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- This model: Strong robustness to typographic attacks, good generalization
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- Check the benchmarks below - or read the 📄 [Latent Crossroads paper](link)
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- ➕
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- New full-auto CLIP-fine-tune suite, (almost) config-free & super fast:
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- Get the code: 👉 [github.com/zer0int/CLIP-fine-tune](https://github.com/zer0int/CLIP-fine-tune)
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- Dataset heuristics (will infer dataset from local or HuggingFace automatically)
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- Loads HuggingFace models, pickles, state dicts / local safetensors, ...
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- Geometry analysis tools: get human-language answers to 'what went wrong', if it did
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Love ❤️ this CLIP?
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</details>
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### 📊 Standard Benchmark Evaluation
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🌟 = This Model
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