Text-to-Image
Diffusers
Safetensors
Diffusion Single File
English
Chinese
MOSSImagePipeline
unsloth
fp8
int8
quantized
moss-image
Instructions to use unsloth/MOSS-Image-Base-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use unsloth/MOSS-Image-Base-FP8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("unsloth/MOSS-Image-Base-FP8", dtype=torch.bfloat16, device_map="cuda") prompt = "a photoreal close-up portrait of an older fisherman, weathered skin, sharp catchlights in the eyes, natural window light, 85mm lens (INT8-ConvRot)" image = pipe(prompt).images[0] - Diffusion Single File
How to use unsloth/MOSS-Image-Base-FP8 with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Unsloth Desktop
File size: 412 Bytes
599abab | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"_class_name": "MOSSImagePipeline",
"_diffusers_version": "0.38.0",
"scheduler": [
"pipeline_moss_image",
"MOSSImageScheduler"
],
"text_encoder": [
"transformers",
"Qwen3_5Model"
],
"tokenizer": [
"transformers",
"Qwen2Tokenizer"
],
"transformer": [
"pipeline_moss_image",
"MOSSImageTransformer"
],
"vae": [
"diffusers",
"AutoencoderKLFlux2"
]
}
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