CLIP-KO-LITE-TypoAttack-Attn-Dropout-ViT-L-14

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# 🌱 CLIP-KO-LITE is slightly less robust, but the Text Encoder won't produce OOD embeddings.
- 📝 Read the [paper](https://github.com/zer0int/CLIP-fine-tune/blob/CLIP-vision/KO-CLIP-teaser/KO-CLIP-paper-final.pdf) (PDF) here.
- If you're looking for a a Text Encoder, you'll probably want these:
- 🖼️ Download [The Text Encoder for generative AI](https://huggingface.co/zer0int/CLIP-KO-LITE-TypoAttack-Attn-Dropout-ViT-L-14/resolve/main/ViT-L-14-KO-LITE-HuggingFace-TE-only.safetensors?download=true)
- 🖼️ Download an [alternatve Text Encoder without Adversarial Training](https://huggingface.co/zer0int/CLIP-KO-LITE-TypoAttack-Attn-Dropout-ViT-L-14/resolve/main/ViT-L-14-KO___NO-ADV___HF-TE-only.safetensors?download=true)
- 🤓 Wanna fine-tune yourself? Get the [code](https://github.com/zer0int/CLIP-fine-tune) on my GitHub.
- Included: Code for fine-tuning and all benchmarks / claims (as per the paper)

## 👉 Check out the [KO variant ](https://huggingface.co/zer0int/CLIP-KO-TypoAttack-Attn-Dropout-ViT-L-14) of this model (strict)

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<summary>👉 CLICK ME to expand example benchmark code ⚡💻</summary>