OzzyGT/MOSS_Image_Base_sdnq_dynamic_8bit
text-to-image model by OzzyGT
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Model card & documentation
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Left: original bf16 · Right: this INT8 model (same prompt and seed). This is a dynamic 8-bit quantized version of OpenMOSS-Team/MOSS-Image-Base using SDNQ. Both the transformer and the Qwen3.5 text encoder are quantized; the VAE is kept unquantized. Note: You need SDNQ v0.2.8 or superior and diffusers from main (0.41.0.dev0 or later). You can find ready-to-use scripts in the diffusers-recipes repository. MOSS-Image runs as a Modular Diffusers pipeline built from the MOSS-Image custom blocks, which load the transformer code shipped in this repository (hence trustremotecode and trustcomponentscode). The VAE runs in float32, like the original. Note: both flags run Python code downloaded from the Hub: trustremotecode=True runs the code of the blocks repository, and trustcomponentscode=True runs the code shipped in the componentsrepo. Only use them with repositories you trust, and review their code before passing different ones. Import sdnq before loading so the quantized weights are registered. The whole pipeline…
Read the full model card ↗ · Preview checked 2026-10-29T07:02:45.863Z
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Model overview
OzzyGT/MOSS_Image_Base_sdnq_dynamic_8bit is a text-to-image model repository published by OzzyGT on Hugging Face. The source reports the diffusers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-image
- Library
- diffusers
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 5,087,229,952
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-20T06:29:15.000Z
- Last modified
- 2026-10-20T06:36:42.000Z
Compatibility and lineage
Reported languages: en
Reported base models: OpenMOSS-Team/MOSS-Image-Base
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-20T06:43:37.702Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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