Instructions to use fal/FLUX.2-Tiny-AutoEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/FLUX.2-Tiny-AutoEncoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/FLUX.2-Tiny-AutoEncoder", 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
Add Diffusers AutoModel support
Browse files- config.json +3 -0
config.json
CHANGED
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@@ -1,6 +1,9 @@
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{
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"_class_name": "Flux2TinyAutoEncoder",
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"_diffusers_version": "0.35.2",
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"act_fn": "silu",
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"decoder_block_out_channels": [
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64,
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{
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"_class_name": "Flux2TinyAutoEncoder",
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"_diffusers_version": "0.35.2",
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"auto_map": {
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"AutoModel": "flux2_tiny_autoencoder.Flux2TinyAutoEncoder"
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},
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"act_fn": "silu",
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"decoder_block_out_channels": [
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64,
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