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README.md

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+# Model Card for EpiDiff
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+<!-- Provide a quick summary of what the model is/does. -->
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+[EpiDiff](https://huanngzh.github.io/EpiDiff/) is a generative model based on Zero123 that takes an image of an object as a conditioning frame, and generates 16 multiviews of that object.
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+![image/gif](https://cdn-uploads.huggingface.co/production/uploads/6375d136dee28348a9c63cbf/1bJcM1NyflPWO4C1HDHPM.gif)
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+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Model type:** Generative image-to-multiview model
+- **License:** [More Information Needed]
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
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+- **Repository:** https://github.com/huanngzh/EpiDiff
+- **Paper:** https://arxiv.org/abs/2312.06725
+- **Demo:** https://huanngzh.github.io/EpiDiff/
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+For usage instructions, please refer to [our EpiDiff GitHub repository](https://github.com/huanngzh/EpiDiff).
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+## Training Details
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+### Training Data
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+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+We use renders from the LVIS dataset, utilizing [huanngzh/render-toolbox](https://github.com/huanngzh/render-toolbox).