HiDream-I1 is HiDream-ai's downloadable text-to-image model family with a 17-billion-parameter image model. The developer publishes Full, Dev, and Fast weights on Hugging Face and supplies an inference repository for local use. Its transformer weights are MIT-licensed, while the included pipeline components have their own documented license terms. Project repository Full model card
What are the key facts about HiDream-I1 downloads?
| Field | Verified information |
|---|---|
| Developer | HiDream-ai. Project repository |
| Released | April 7, 2025. Project repository |
| Type | Text-to-image diffusion family with Full and distilled Dev/Fast versions. Project repository |
| Size or parameters | 17 billion parameters for the image model. Full model card |
| License and access | MIT transformer weights; VAE and text-encoder licenses are separate. Official downloads are under HiDream-ai. Full card Dev card Fast card
|
| Where it runs | Developer's CUDA Python scripts, a local Gradio demo, and a documented Diffusers integration. Project repository |
Before downloading, decide whether your goal is to reproduce the Python example or use a visual workflow. The sibling HiDream-I1 ComfyUI setup guide covers that interface's packaged files. The steps here follow the developer's Python repository.
Which official HiDream-I1 files and examples are available?
The download structure makes the available variants explicit. HiDream-I1-Full, HiDream-I1-Dev, and HiDream-I1-Fast each have an official model card, and the project links the corresponding repositories. This gives you a clear source for recording which weights produced an image. Full card Dev card Fast card
The developer supplies runnable examples and a local Gradio application. That provides two practical entry points after the environment is installed: a script for a repeatable baseline or an interface for entering prompts interactively. The repository also documents a Diffusers route for Python integration. Project repository
HiDream's model card describes multiple visual styles and publishes prompt-following evaluations. Use a simple original scene for an installation check, then decide whether the model meets your visual requirements through a separate review. An installation is successful when the expected pipeline runs and saves an output; that does not automatically establish creative suitability. Full model card
What dependencies affect a local HiDream-I1 installation?
The image-model weights are only part of the setup. The inference repository downloads a Llama text encoder and warns that its model terms must be accepted through your Hugging Face account. Authenticate that account before interpreting a gated-model error as a corrupted HiDream download. Project repository
The model card identifies separate components and licenses, including the VAE and text encoders. Preserve those notices in your deployment record instead of describing the complete pipeline solely by the transformer's MIT label. The practical access consequence is that the Llama component has its own agreement and download conditions. Full model card
The official script uses CUDA and loads multiple model components. A successful file download does not prove that the pipeline fits your GPU memory. Diffusers documents offloading techniques and their performance tradeoffs, but apply them through the relevant supported integration rather than assuming they alter every repository script automatically. Inference source Memory guide
Track downloading, dependency installation, authentication, and model loading as separate setup stages. Note which stage fails before retrying, and keep completed downloads while you investigate a dependency or access problem.
How do you download HiDream-I1 and run the Python example?
Start at the HiDream-ai project repository and choose a checkpoint from its model table. For a first setup, choose one variant and record its repository identifier; downloading every variant is unnecessary for confirming that your environment works. Project repository
Prepare a compatible Python environment and follow the project's PyTorch and CUDA requirements. The README recommends CUDA 12.4 for manual installation and requires Flash Attention for the repository path. Clone the project before installing requirements.txt, since that file belongs to the checkout. Project repository
git clone https://github.com/HiDream-ai/HiDream-I1
cd HiDream-I1
python -m pip install -r requirements.txt
python -m pip install -U flash-attn --no-build-isolation
python -m pip install -U huggingface_hub
hf auth login
hf download HiDream-ai/HiDream-I1-Dev
python inference.py --model_type dev
Accept the required Llama model terms before the inference command. hf auth login is the current CLI's documented authentication command; the project README uses the earlier huggingface-cli login spelling. Authenticate the same account that has access to the encoder. Project repository CLI documentation
The hf download command above prefetches Dev into the default Hugging Face cache. The official script selects HiDream-ai/HiDream-I1-Dev when you pass --model_type dev, so its repository-based loading can use that cache. This command does not prefetch every separate dependency. CLI documentation Inference source
If you prefer a visible download directory for archiving, the CLI also supports --local-dir. Keep the repository layout intact, and understand that creating an arbitrary local directory does not automatically change the script's configured repository paths. Modify the relevant loading path deliberately when adapting the code to a local archive. CLI documentation Inference source
Let the supplied example complete before changing its prompt. The script writes output.png in the working directory. Confirm that the image exists and opens, then save the run's variant, software versions, and settings before making another experiment. Inference source
For Full or Fast, use the corresponding --model_type value and allow the script to select its associated configuration. Its variant table sets both the weights and generation parameters. Avoid manually mixing one checkpoint with another variant's settings during the installation check. Inference source
For interactive use after setup, install Gradio with python -m pip install gradio, then run the developer's python gradio_demo.py. Gradio installation Demo source The Gradio interface is a way to operate the local model; a browser window alone does not mean inference is being supplied by a remote service. Project repository
If a run fails, preserve the first useful error and identify its stage. Check authentication for access failures, the selected repository for missing files, dependencies for import failures, and memory for allocation errors. This sequence is a suggested troubleshooting method that keeps unrelated changes out of the same retry.
How do HiDream-I1 and Qwen-Image installation requirements differ?
Qwen-Image also publishes weights with a Diffusers generation example, under Apache 2.0. HiDream's official setup specifically documents its Llama encoder access requirement and offers the three named generation variants. Those differences matter when planning a clean installation or reproducing another developer's setup. Qwen model card HiDream repository
For broader workflow context, the ComfyUI pillar explains a visual alternative to scripts. Compare installation effort and useful output on your actual hardware rather than treating a model's name or parameter count as a complete deployment specification.
What should you check before downloading HiDream-I1?
Where should I download HiDream-I1?
Download HiDream-I1 from the Full, Dev, or Fast Hugging Face repositories linked by the official HiDream-ai project. Save the complete repository identifier and revision with your deployment notes. Project repository
Why does HiDream-I1 ask for access to Llama?
The official HiDream-I1 inference pipeline uses a Llama text encoder. Its setup requires accepting that component's model agreement and authenticating with an authorized Hugging Face account. Project repository
Does downloading HiDream-I1 Dev also download Full?
HiDream-I1 Full, Dev, and Fast have separate repository identifiers. Downloading Dev does not download the Full or Fast checkpoint. Full card Dev card Fast card
Can I run HiDream-I1 from an arbitrary download folder?
Run the official HiDream-I1 example from the cloned project with its dependencies installed. The script loads configured repository paths, while the Hugging Face CLI's --local-dir option only controls download placement; update the loading paths if you adapt it to a local archive. Inference source CLI documentation
Top comments (0)