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--- |
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license: apache-2.0 |
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pipeline_tag: text-to-image |
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--- |
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# Chroma1-HD |
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Chroma1-HD is an **8.9B** parameter text-to-image foundational model based on **FLUX.1-schnell**. It is fully **Apache 2.0 licensed**, ensuring that anyone can use, modify, and build upon it. |
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As a **base model**, Chroma1 is intentionally designed to be an excellent starting point for **finetuning**. It provides a strong, neutral foundation for developers, researchers, and artists to create specialized models. |
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for the fast CFG "baked" version please go to [Chroma1-Flash](https://huggingface.co/lodestones/Chroma1-Flash). |
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### Key Features |
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* **High-Performance Base:** 8.9B parameters, built on the powerful FLUX.1 architecture. |
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* **Easily Finetunable:** Designed as an ideal checkpoint for creating custom, specialized models. |
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* **Community-Driven & Open-Source:** Fully transparent with an Apache 2.0 license, and training history. |
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* **Flexible by Design:** Provides a flexible foundation for a wide range of generative tasks. |
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## Special Thanks |
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A massive thank you to our supporters who make this project possible. |
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* **Anonymous donor** whose incredible generosity funded the pretraining run and data collections. Your support has been transformative for open-source AI. |
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* **Fictional.ai** for their fantastic support and for helping push the boundaries of open-source AI. You can try Chroma on their platform: |
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[](https://fictional.ai/?ref=chroma_hf) |
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## How to Use |
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### `diffusers` Library |
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```python |
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import torch |
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from diffusers import ChromaPipeline |
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pipe = ChromaPipeline.from_pretrained("lodestones/Chroma1-HD", torch_dtype=torch.bfloat16) |
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pipe.enable_model_cpu_offload() |
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prompt = [ |
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"A high-fashion close-up portrait of a blonde woman in clear sunglasses. The image uses a bold teal and red color split for dramatic lighting. The background is a simple teal-green. The photo is sharp and well-composed, and is designed for viewing with anaglyph 3D glasses for optimal effect. It looks professionally done." |
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] |
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negative_prompt = ["low quality, ugly, unfinished, out of focus, deformed, disfigure, blurry, smudged, restricted palette, flat colors"] |
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image = pipe( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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generator=torch.Generator("cpu").manual_seed(433), |
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num_inference_steps=40, |
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guidance_scale=3.0, |
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num_images_per_prompt=1, |
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).images[0] |
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image.save("chroma.png") |
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``` |
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ComfyUI |
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For advanced users and customized workflows, you can use Chroma with ComfyUI. |
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**Requirements:** |
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* A working ComfyUI installation. |
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* [Chroma checkpoint](https://huggingface.co/lodestones/Chroma) (latest version). |
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* [T5 XXL Text Encoder](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors). |
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* [FLUX VAE](https://huggingface.co/lodestones/Chroma/resolve/main/ae.safetensors). |
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* [Chroma Workflow JSON](https://huggingface.co/lodestones/Chroma/resolve/main/ChromaSimpleWorkflow20250507.json). |
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**Setup:** |
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1. Place the `T5_xxl` model in your `ComfyUI/models/clip` folder. |
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2. Place the `FLUX VAE` in your `ComfyUI/models/vae` folder. |
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3. Place the `Chroma checkpoint` in your `ComfyUI/models/diffusion_models` folder. |
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4. Load the Chroma workflow file into ComfyUI and run. |
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## Model Details |
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* **Architecture:** Based on the 8.9B parameter FLUX.1-schnell model. |
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* **Training Data:** Trained on a 5M sample dataset curated from a 20M pool, including artistic, photographic, and niche styles. |
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* **Technical Report:** A comprehensive technical paper detailing the architectural modifications and training process is forthcoming. |
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## Intended Use |
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Chroma is intended to be used as a **base model** for researchers and developers to build upon. It is ideal for: |
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* Finetuning on specific styles, concepts, or characters. |
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* Research into generative model behavior, alignment, and safety. |
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* As a foundational component in larger AI systems. |
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## Limitations and Bias Statement |
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Chroma is trained on a broad, filtered dataset from the internet. As such, it may reflect the biases and stereotypes present in its training data. The model is released in a state as is and has not been aligned with a specific safety filter. |
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Users are responsible for their own use of this model. It has the potential to generate content that may be considered harmful, explicit, or offensive. I encourage developers to implement appropriate safeguards and ethical considerations in their downstream applications. |
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## Summary of Architectural Modifications |
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*(For a full breakdown, tech report soon-ish.)* |
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* **12B → 8.9B Parameters:** |
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* **TL;DR:** I replaced a 3.3B parameter timestep-encoding layer with a more efficient 250M parameter FFN, as the original was vastly oversized for its task. |
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* **MMDiT Masking:** |
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* **TL;DR:** Masking T5 padding tokens enhanced fidelity and increased training stability by preventing the model from focusing on irrelevant `<pad>` tokens. |
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* **Custom Timestep Distributions:** |
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* **TL;DR:** I implemented a custom timestep sampling distribution (`-x^2`) to prevent loss spikes and ensure the model trains effectively on both high-noise and low-noise regions. |
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## P.S |
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Chroma1-HD is Chroma-v.50 |
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## Citation |
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``` |
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@misc{rock2025chroma, |
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author = {Lodestone Rock}, |
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title = {Chroma1-HD}, |
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year = {2025}, |
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publisher = {Hugging Face}, |
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journal = {Hugging Face repository}, |
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howpublished = {\url{https://huggingface.co/lodestones/Chroma1-HD}}, |
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} |
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``` |
