Unverified Commit 174cf868 authored by XCL's avatar XCL Committed by GitHub
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Tencent Hunyuan Team - Updated Doc for HunyuanDiT (#8383)

* add hunyuandit doc

* update hunyuandit doc

* update hunyuandit 2d model

* update toctree.yml for hunyuandit
parent 41360440
......@@ -242,6 +242,8 @@
title: PixArtTransformer2D
- local: api/models/dit_transformer2d
title: DiTTransformer2D
- local: api/models/hunyuan_transformer_2d
title: HunyuanDiT2DModel
- local: api/models/transformer_temporal
title: Transformer Temporal
- local: api/models/prior_transformer
......@@ -289,6 +291,8 @@
title: DiffEdit
- local: api/pipelines/dit
title: DiT
- local: api/pipelines/hunyuandit
title: Hunyuan-DiT
- local: api/pipelines/i2vgenxl
title: I2VGen-XL
- local: api/pipelines/pix2pix
......@@ -457,4 +461,4 @@
title: Video Processor
title: Internal classes
isExpanded: false
title: API
\ No newline at end of file
title: API
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# HunyuanDiT2DModel
A Diffusion Transformer model for 2D data from [Hunyuan-DiT](https://github.com/Tencent/HunyuanDiT).
## HunyuanDiT2DModel
[[autodoc]] HunyuanDiT2DModel
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# Hunyuan-DiT
![chinese elements understanding](https://github.com/gnobitab/diffusers-hunyuan/assets/1157982/39b99036-c3cb-4f16-bb1a-40ec25eda573)
[Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding](https://arxiv.org/abs/2405.08748)] from Tencent Hunyuan.
The abstract from the paper is:
*We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transformer structure, text encoder, and positional encoding. We also build from scratch a whole data pipeline to update and evaluate data for iterative model optimization. For fine-grained language understanding, we train a Multimodal Large Language Model to refine the captions of the images. Finally, Hunyuan-DiT can perform multi-turn multimodal dialogue with users, generating and refining images according to the context. Through our holistic human evaluation protocol with more than 50 professional human evaluators, Hunyuan-DiT sets a new state-of-the-art in Chinese-to-image generation compared with other open-source models.*
You can find the original codebase at [Tencent/HunyuanDiT](https://github.com/Tencent/HunyuanDiT) and all the available checkpoints at [Tencent-Hunyuan](https://huggingface.co/Tencent-Hunyuan/HunyuanDiT).
**Highlights**: HunyuanDiT supports Chinese/English-to-image, multi-resolution generation.
HunyuanDiT has the following components:
* It uses a diffusion transformer as the backbone
* It combines two text encoders, a bilingual CLIP and a multilingual T5 encoder
## HunyuanDiTPipeline
[[autodoc]] HunyuanDiTPipeline
- all
- __call__
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