Text-to-Image
Diffusers
Safetensors
Flux2Pipeline
quantized
mxfp4
autoround
diffusion
autoquant-agent
Instructions to use INCModel3/FLUX.2-dev-MXFP4-RTN-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use INCModel3/FLUX.2-dev-MXFP4-RTN-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("INCModel3/FLUX.2-dev-MXFP4-RTN-AutoRound", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/generation_config.json from INCModel3/FLUX.2-dev-MXFP4-RTN-AutoRound: direct link, hf CLI and curl.
- Browser
- Download file 155 Bytes
-
https://huggingface.co/INCModel3/FLUX.2-dev-MXFP4-RTN-AutoRound/resolve/main/text_encoder/generation_config.json
- Command line
-
hf download hf://INCModel3/FLUX.2-dev-MXFP4-RTN-AutoRound/text_encoder/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/INCModel3/FLUX.2-dev-MXFP4-RTN-AutoRound/resolve/main/text_encoder/generation_config.json
155 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "do_sample": true, | |
| "eos_token_id": 2, | |
| "temperature": 0.15, | |
| "transformers_version": "5.14.1" | |
| } | |