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README.md

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----
-license: mit
----
+---
+license: mit
+pipeline_tag: video-to-video
+library_name: pytorch
+tags:
+  - computer-vision
+  - video
+  - video-frame-interpolation
+  - vfi
+  - video-to-video
+  - comfyui
+  - pytorch
+---
+
+# SnJake Sapsan-VFI
+
+Sapsan-VFI is a **x2 frame interpolation** model for video. It inserts a single middle frame between every input pair, effectively doubling the FPS.
+
+## Examples
+
+https://cdn-uploads.huggingface.co/production/uploads/658814fd586088fd274d8cc1/nVeeIIS4p-ngRWRUMO_6W.mp4
+
+https://cdn-uploads.huggingface.co/production/uploads/658814fd586088fd274d8cc1/B79GJN0rHXRozNTXYP0Od.mp4
+
+
+https://cdn-uploads.huggingface.co/production/uploads/658814fd586088fd274d8cc1/Q5-LEo5SkAuyfjXcd4iCB.mp4
+
+## How to use in ComfyUI
+
+The model is designed to work with the **Sapsan-VFI** ComfyUI node.
+
+1. Install the node from the GitHub repo: `https://github.com/SnJake/SnJake_Sapsan-VFI`.
+2. Download the weights from this repository.
+3. Place the file(s) into `ComfyUI/models/sapsan_vfi/`.
+4. Select the weights in the node dropdown and run the workflow.
+
+Recommended workflow:
+
+Example workflow can be found in `Example Workflow` folder in Git repo.
+
+
+Notes:
+- The node has a `console_progress` toggle to print progress in the ComfyUI console.
+
+## Weights
+
+- `Sapsan-VFI.safetensors`
+- `Sapsan-VFI.pt`
+
+## Training Details
+
+- Created out of curiosity and personal interest.
+- Total epochs: **11**
+- Dataset: **2700 videos**
+- Shards: **151** shards of **1000** shadrs in each. 151 000 triplets.
+
+Training code is included in `training_code/` for reference.
+
+## Disclaimer
+
+This project was made purely for curiosity and personal interest. The code was written by GPT-5.2 Codex.