Instructions to use Jommarn/FLUX.2-Klein-4B-Kleinfetti with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jommarn/FLUX.2-Klein-4B-Kleinfetti with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jommarn/FLUX.2-Klein-4B-Kleinfetti", 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
FLUX.2 Klein 4B - Kleinfetti
Complete FLUX.2 Klein 4B - Kleinfetti pipeline with fine-tuned anime and art-style transformer backbone, text encoders, tokenizer, and VAE.
Files Included
kleinfetti_klenfetti260503.safetensors: Full fine-tuned model checkpoint (7.75 GB)text_encoder/: Base text encoders fromblack-forest-labs/FLUX.2-klein-base-4Btokenizer/: Tokenizer filesvae/: 16-channel Flux VAEscheduler/: Scheduler configurationmodel_index.json: Pipeline configuration
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Model tree for Jommarn/FLUX.2-Klein-4B-Kleinfetti
Base model
black-forest-labs/FLUX.2-klein-base-4B