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flux1-torch-int8
imgailab/flux1-torch-int8
flux1-torch-int8 is a text-to-image model from imgailab. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as apache-2.0.
This is a INT8 pytorch version of black-forest-labs/FLUX.1-schnell.
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12.3 GB
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At a glance
- Task
- Text-to-Image
- Library
- diffusers
- License
- apache-2.0
- Access
- Public
- Created
- Aug 9, 2025
- Updated
- Aug 9, 2025
- SHA
- 11580a00
Base models
Model card
From the Hugging Face model README
FLUX.1 Schnell - PyTorch INT8
This is a INT8 pytorch version of black-forest-labs/FLUX.1-schnell.
Model Details
- Model Type: FLUX.1 Schnell
- Parameters: 12B
- Backend: PyTorch
- Quantization: INT8
- Memory Usage: ~12.0GB
- Conversion Date: 2025-08-09
Usage
PyTorch INT8
# PyTorch INT8 quantized model
from diffusers import FluxPipeline
import torch
# Load INT8 quantized model
pipe = FluxPipeline.from_pretrained(
"Mitchins/flux1-torch-int8",
torch_dtype=torch.qint8,
use_safetensors=True
)
# For CPU inference
pipe = pipe.to("cpu")
# Generate image
image = pipe("A beautiful landscape", num_inference_steps=20).images[0]
image.save("output.png")
Performance
| Backend | Quantization | Memory | Speed (CPU) | Speed (GPU) | Quality |
|---|---|---|---|---|---|
| PyTorch | INT8 | ~12.0GB | Good | Fast | Slightly Reduced |
Limitations
- INT8 quantization may slightly reduce image quality
- Best suited for CPU inference or memory-constrained environments
Citation
@misc{flux1-pytorch-int8,
title = {FLUX.1 Schnell PyTorch INT8}
author = {ImageAI Server Contributors}
year = {2024}
publisher = {HuggingFace}
url = {https://huggingface.co/Mitchins/flux1-torch-int8}
}
Converted using ImageAI Server Model Converter v1.0
- Task
- Text-to-Image
- Library
- diffusers
- License
- apache-2.0
- Created
- Aug 9, 2025
- Updated
- Aug 9, 2025