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No actionable comments were generated in the recent review. 🎉 ℹ️ Recent review info⚙️ Run configurationConfiguration used: Path: .coderabbit.yaml Review profile: CHILL Plan: Pro Run ID: 📒 Files selected for processing (5)
📝 WalkthroughWalkthroughThe PR modifies five files across text encoding and model architecture components. Changes include: propagating transformer_options through the image patch processing pipeline in the Flux model; adjusting rope-shift configuration to derive from cross-attention context length instead of fixed values; modifying position ID calculations in Qwen text encoding to account for attention masks; extending the LongCat image tokenizer with image padding constants and updating its tokenization method to handle image parameters; and adding a reordering step in Qwen VL's forward pass to restore windowed sequence ordering. 🚥 Pre-merge checks | ✅ 1 | ❌ 2❌ Failed checks (1 warning, 1 inconclusive)
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| hidden_states = block(hidden_states, position_embeddings, cu_seqlens_now, optimized_attention=optimized_attention) | ||
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| hidden_states = self.merger(hidden_states) | ||
| # Potentially important for spatially precise edits. This is present in the HF implementation. |
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The output still appears nice without having this change. However, the numerical precision (cosine distance) between the original implementation and this one jumps by a significant amount when adding this part.
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Does it support turbo?LongCat-Image-Edit-Turbo |
I haven't tested it, but it should work since it's using the same workflow/pipeline. I've repackaged the turbo model here: Modify the provided workflow to use this model instead. |
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Thanks , how it the fp8 quality, fp8 smaller and faster normally |
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Is it still a single image edit model? |
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Has anyone tried Longcat image edit turbo? Compared to the non‑turbo version, which one is actually worth keeping? |
Minor difference, about four times faster. |
Repackaged model: https://huggingface.co/TalmajM/LongCat-Image-Edit_ComfyUI_repackaged/tree/main
Workflow: longcat_image_edit final.json
The outputs differ slightly from the original, because we pre-process the input image using existing comfy nodes.