Instructions to use tiny-random/flux-3-image-klein-comfy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tiny-random/flux-3-image-klein-comfy with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tiny-random/flux-3-image-klein-comfy", 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
File size: 1,609 Bytes
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"_class_name": "Flux3DistilledModularPipeline",
"_blocks_class_name": "Flux3DistilledAutoBlocks",
"transformer": [
"diffusers",
"Flux3Transformer2DModel",
{
"type_hint": [
"diffusers",
"Flux3Transformer2DModel"
],
"pretrained_model_name_or_path": ".",
"subfolder": "transformer"
}
],
"vae": [
"diffusers",
"AutoencoderKLFlux2",
{
"type_hint": [
"diffusers",
"AutoencoderKLFlux2"
],
"pretrained_model_name_or_path": ".",
"subfolder": "vae"
}
],
"text_encoder": [
"transformers",
"Qwen3VLForConditionalGeneration",
{
"type_hint": [
"transformers",
"Qwen3VLForConditionalGeneration"
],
"pretrained_model_name_or_path": ".",
"subfolder": "text_encoder"
}
],
"tokenizer": [
"transformers",
"AutoProcessor",
{
"type_hint": [
"transformers",
"AutoProcessor"
],
"pretrained_model_name_or_path": ".",
"subfolder": "tokenizer"
}
],
"prompt_upsampler": [
"transformers",
"Qwen3_5ForConditionalGeneration",
{
"type_hint": [
"transformers",
"Qwen3_5ForConditionalGeneration"
],
"pretrained_model_name_or_path": ".",
"subfolder": "prompt_upsampler"
}
],
"prompt_upsampler_processor": [
"transformers",
"AutoProcessor",
{
"type_hint": [
"transformers",
"AutoProcessor"
],
"pretrained_model_name_or_path": ".",
"subfolder": "prompt_upsampler_processor"
}
]
}
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