HiDream E1 Full

--- license: mit tags: - image-editing - HiDream.ai language: - en pipeline_tag: any-to-any library_name: diffusers base_model: - HiDream-ai/HiDream-I1-Full ---  HiDream-E1 is an image editing model built on [HiDream-I1](https://github.com/HiDream-ai/HiDream-I1). <!--  --> <span style="color: #FF5733; font-weight: bold">For more features and to experience the full capabilities of our product, please visit [https://vivago.ai/](https://vivago.ai/).</span> ## Project Updates - 🌟 **July 16, 2025**: We've open-sourced the updated image editing model [**HiDream-E1.1**](https://huggingface.co/HiDream-ai/HiDream-E1-1). - 📝 **May 28, 2025**: We've released our technical report [HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer](https://arxiv.org/abs/2505.22705). - 🚀 **April 28, 2025**: We've open-sourced the instruction-based image editing model **HiDream-E1**. ## Quick Start Please make sure you have installed [Flash Attention](https://github.com/Dao-AILab/flash-attention) and latest [Diffusers](https://github.com/huggingface/diffusers.git). We recommend CUDA versions 12.4 for the manual installation. ```sh pip install -r requirements.txt pip install -U flash-attn --no-build-isolation pip install -U git+https://github.com/huggingface/diffusers.git ``` Then you can run the inference scripts to generate images: ``` python python ./inference.py ``` Alternatively, you can use the model in your own code: ```python import torch from transformers import PreTrainedTokenizerFast, LlamaForCausalLM from pipeline_hidream_image_editing import HiDreamImageEditingPipeline from PIL import Image # Load the tokenizer and text encoder tokenizer_4 = PreTrainedTokenizerFast.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") text_encoder_4 = LlamaForCausalLM.from_pretrained( "meta-llama/Llama-3.1-8B-Instruct", output_hidden_states=True, output_attentions=True, torch_dtype=torch.bfloat16, ) # Load the HiDream pipeline pipe = HiDreamImageEditingPipeline.from_pretrained( "HiDream-ai/HiDream-E1-Full", tokenizer_4=tokenizer_4, text_encoder_4=text_encoder_4, torch_dtype=torch.bfloat16, ) # Load and prepare input image test_image = Image.open("your_image.jpg") test_image = test_image.resize((768, 768)) # Move pipeline to GPU pipe = pipe.to("cuda", torch.bfloat16) # Genera...

Source context: 228 downloads · 217 likes · Pipeline any-to-any · Library diffusers · Repo HiDream-ai/HiDream-E1-Full

Source context: 196 downloads · 216 likes · Pipeline any-to-any · Library diffusers · Repo HiDream-ai/HiDream-E1-Full