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README.md

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----
-license: mit
----
+---
+license: mit
+pipeline_tag: image-to-image
+library_name: onnxruntime
+tags:
+  - onnx
+  - rife
+  - frame-interpolation
+  - video
+  - motion-interpolation
+---
+
+# RIFE_FP32
+
+RIFE_FP32 is an ONNX export of a RIFE frame interpolation model intended for video frame generation and FPS upscaling workflows.
+
+## Model Description
+
+This repository provides a float32 ONNX version of a RIFE model for frame interpolation.  
+It is intended for use in applications that generate intermediate frames between two input video frames in order to increase perceived smoothness or raise output framerate.
+
+## File
+
+- `RIFE_fp32.onnx`
+
+## Intended Use
+
+This model is intended for:
+
+- video frame interpolation
+- FPS upscaling workflows
+- offline processing pipelines
+- ONNX Runtime based applications
+
+Example use cases include:
+
+- converting 24 FPS video to higher framerates
+- generating in-between frames for smoother playback
+- integrating frame interpolation into custom desktop tools or video pipelines
+
+## Input / Output
+
+The model is expected to take paired frame data prepared by the calling application and output interpolated intermediate frames.
+
+Exact tensor formatting, preprocessing, and batching may depend on the application using the model.
+
+## Usage Notes
+
+- Designed for ONNX Runtime inference
+- Best suited for integration into custom frame interpolation pipelines
+- Performance depends on hardware, ONNX Runtime provider, and input resolution
+- CUDA, DirectML, ROCm, or CPU execution may be used depending on the environment
+
+## Limitations
+
+- Quality may vary on fast motion, occlusion boundaries, transparency, particles, or scene cuts
+- Results depend heavily on preprocessing and postprocessing in the host application
+- This repository provides the model file only, not a full standalone interpolation application
+
+## License
+
+This model repository is released under the MIT License.
+
+## Acknowledgments
+
+RIFE is widely used for video frame interpolation research and practical workflows.  
+This repository provides an ONNX-packaged version for deployment and application integration.