Instructions to use mann-e/mann-e_flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mann-e/mann-e_flux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mann-e/mann-e_flux", 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
- Draw Things
- DiffusionBee
File size: 574 Bytes
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"_class_name": "FluxPipeline",
"_diffusers_version": "0.32.0.dev0",
"_name_or_path": "./mann-e_flux",
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"text_encoder_2": [
"transformers",
"T5EncoderModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"tokenizer_2": [
"transformers",
"T5TokenizerFast"
],
"transformer": [
"diffusers",
"FluxTransformer2DModel"
],
"vae": [
"diffusers",
"AutoencoderTiny"
]
}
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