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README.md

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+---
+license: mit
+language:
+- en
+library_name: diffusers
+---
+
+# Arc2Face Model Card
+
+<div align="center">
+
+[**Project Page**](https://arc2face.github.io/) **|** [**Paper (ArXiv)**](https://arxiv.org/abs/2403.11641) **|** [**Code**](https://github.com/foivospar/Arc2Face) **|** [🤗 **Gradio demo**](https://huggingface.co/spaces/FoivosPar/Arc2Face)
+
+
+
+</div>
+
+## Introduction
+
+Arc2Face is an ID-conditioned face model, that can generate diverse, ID-consistent photos of a person given only its ArcFace ID-embedding.
+It is trained on a restored version of the WebFace42M face recognition database, and is further fine-tuned on FFHQ and CelebA-HQ.
+
+<div  align="center">
+<img src='assets/samples_short.jpg'>
+</div>
+
+## Model Details
+
+It consists of 2 components:
+- encoder, a finetuned CLIP ViT-L/14 model
+- arc2face, a finetuned UNet model
+
+both of which are fine-tuned from [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5).
+The encoder is tailored for projecting ID-embeddings to the CLIP latent space.
+Arc2Face adapts the pre-trained backbone to the task of ID-to-face generation, conditioned solely on ID vectors.
+
+## Usage
+
+The models can be downloaded directly from this repository or using python:
+```python
+from huggingface_hub import hf_hub_download
+
+hf_hub_download(repo_id="FoivosPar/Arc2Face", filename="arc2face/config.json", local_dir="./models")
+hf_hub_download(repo_id="FoivosPar/Arc2Face", filename="arc2face/diffusion_pytorch_model.safetensors", local_dir="./models")
+hf_hub_download(repo_id="FoivosPar/Arc2Face", filename="encoder/config.json", local_dir="./models")
+hf_hub_download(repo_id="FoivosPar/Arc2Face", filename="encoder/pytorch_model.bin", local_dir="./models")
+```
+
+Please check our [GitHub repository](https://github.com/foivospar/Arc2Face) for complete inference instructions.
+
+## Limitations and Bias
+
+- Only one person per image can be generated.
+- Poses are constrained to the frontal hemisphere, similar to FFHQ images.
+- The model may reflect the biases of the training data or the ID encoder.
+
+## Citation
+
+
+**BibTeX:**
+
+```bibtex
+@misc{paraperas2024arc2face,
+      title={Arc2Face: A Foundation Model of Human Faces}, 
+      author={Foivos Paraperas Papantoniou and Alexandros Lattas and Stylianos Moschoglou and Jiankang Deng and Bernhard Kainz and Stefanos Zafeiriou},
+      year={2024},
+      eprint={2403.11641},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```

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