Chroma1-HD-GGUF

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.

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.

for the fast CFG "baked" version please go to Chroma1-Flash.

Key Features High-Performance Base: 8.9B parameters, built on the powerful FLUX.1 architecture. Easily Finetunable: Designed as an ideal checkpoint for creating custom, specialized models. Community-Driven & Open-Source: Fully transparent with an Apache 2.0 license, and training history. Flexible by Design: Provides a flexible foundation for a wide range of generative tasks. Special Thanks A massive thank you to our supporters who make this project possible.

Anonymous donor whose incredible generosity funded the pretraining run and data collections. Your support has been transformative for open-source AI. Fictional.ai for their fantastic support and for helping push the boundaries of open-source AI. You can try Chroma on their platform: https://fictional.ai/?ref=chroma_hf

Summary of Architectural Modifications (For a full breakdown, tech report soon-ish.)

12B → 8.9B Parameters: 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. MMDiT Masking: TL;DR: Masking T5 padding tokens enhanced fidelity and increased training stability by preventing the model from focusing on irrelevant <pad> tokens. Custom Timestep Distributions: 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. P.S Chroma1-HD is not the old Chroma-v.50 it has been retrained from v.48