SAE = Sparse autoencoder. All training info & code: github.com/zer0int/CLIP-SAE-finetune
This Long-CLIP, 👉 direct download Text Encoder 👈 is also the best Long-CLIP to use with HunyuanVideo.
Required: Use with my zer0int/ComfyUI-HunyuanVideo-Nyan node (changes influence of LLM vs. CLIP; otherwise, difference is very little).
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The original CLIP model has 77 tokens max input - but only ~20 tokens effective length. See the original Long-CLIP paper for details. HunyuanVideo demo:

69 tokens, normal scene:

Lens: 16mm. Aperture: f/2.8. Color Grading: Blue-green monochrome. Lighting: Low-key with backlit silhouettes. Background: Gothic cathedral at night, stained glass windows breaking. Camera angle: Over the shoulder of a ninja, tracking her mid-air leap as she lands on a rooftop.

52 tokens, OOD (Out-of-Distribution) scene: Superior handling for consistency and prompt-following despite OOD concept.

In this surreal nightmare documentary, a sizable spider with a human face is peacefully savoring her breakfast at a diner. The spider has a spider body, but a lady's face on the front, and regular human hands at the end of the spider legs.

zer0int/LongCLIP-SAE-ViT-L-14

Long-CLIP ViT-L/14 finetune: SAE-informed adversarial training

zer0int/
LongCLIP-SAE-ViT-L-14