Instructions to use Lakonik/AsymFLUX.2-klein-9B-collection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lakonik/AsymFLUX.2-klein-9B-collection with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lakonik/AsymFLUX.2-klein-9B-collection", 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
Upload 2 files
Browse files
asymflux2_klein_9b_sft_flux2_klein/config.json
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{
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"_class_name": "AsymFlux2Transformer2DModel",
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"_diffusers_version": "0.37.0",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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32,
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32,
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32,
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32
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],
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"base_rank": 128,
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"eps": 1e-06,
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"guidance_embeds": false,
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"in_channels": 3,
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"joint_attention_dim": 12288,
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"mlp_ratio": 3.0,
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"num_attention_heads": 32,
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"num_layers": 8,
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"num_single_layers": 24,
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"num_timesteps": 1,
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"patch_size": 16,
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"rope_theta": 2000,
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"sigma_min": 0.0001,
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"timestep_guidance_channels": 256
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}
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asymflux2_klein_9b_sft_flux2_klein/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e96c777e062ac8f347c82b398796fd129ecb1d3a5ee4edf50a119ed3bdde9b8
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size 707083194
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