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TestingRef2va

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  1. Update app.py Running

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  2. Upload film_net.py

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  4. Upload pk_workflow.py

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  1. feat(app): add auto-canvas selection and update conditioner space⁠

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  2. feat: add Turbo LoRA presets and ComfyUI support⁠

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  3. feat(lora): add ComfyUI MiniMax-H3 LoRA conversion⁠

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  4. Upload app.py

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  1. Update app.py

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  3. Update README.md

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  1. Upload app.py

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  2. Upload app.py

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  3. Update requirements.txt

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  1. Open badge links in a new tab

    multimodalart HF Staff
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  2. Price bookings against the AoTI blocks, generate from 2 s again, cross-link the demos⁠

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  3. Start the duration slider at the 5 s the model actually generates

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  4. Restore probe

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  5. Cache the conditioner client with functools.cache, tidy comments

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  6. Let gradio_client forward the caller's ZeroGPU token itself instead of pinning one by hand

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  7. Forward the caller's ZeroGPU token to the conditioner, plainly

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  8. Bill the conditioner call to the requesting user's own ZeroGPU token, never an org token

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  9. Pay for the conditioner call with the first ZeroGPU identity that can: the caller's token, this Space's HF_TOKEN, then none

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  10. Fall back to an anonymous conditioner call when the forwarded ZeroGPU token is refused

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  11. Forward the caller's ZeroGPU token to the conditioner so one request bills as one request

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  12. Load the AoTI packages from the public multimodalart/minimax-h3-aoti, move the upsample toggle under the prompt

    multimodalart HF Staff
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  13. Migrate to canonical diffusers PR 14371 + public MiniMaxAI/MiniMax-H3 weights, add prompt upsampling toggle

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  1. Update README.md

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  2. Duration slider from 2s

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  3. Lower minimum duration to 2s

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  4. The keyframe half moved to multimodalart/minimax-h3

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  5. Mirror the conditioner's canonical table, grouped by ratio

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  6. Update README.md

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  7. Mirror the conditioner's 16-canvas table (fast 4:3, 3:4 and 21:9 added)

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  8. Point at the public multimodalart/qwen3vl-conditioner, called without a token

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  9. Point at the public multimodalart/qwen3vl-conditioner, called without a token

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  10. Fast canvas stays the default; the examples carry full-resolution canvases

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  11. Full 16:9 as the default canvas; match the conditioner's renamed fast label

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