Feature Extraction
Transformers
Safetensors
Diffusers
English
qwen3
flux
text-encoder
pruning
distillation
Instructions to use SearchingMan/FLUX.2-klein-9B-Text-Encoder-Pruned-5.1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SearchingMan/FLUX.2-klein-9B-Text-Encoder-Pruned-5.1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SearchingMan/FLUX.2-klein-9B-Text-Encoder-Pruned-5.1B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SearchingMan/FLUX.2-klein-9B-Text-Encoder-Pruned-5.1B") model = AutoModel.from_pretrained("SearchingMan/FLUX.2-klein-9B-Text-Encoder-Pruned-5.1B", device_map="auto") - Diffusers
How to use SearchingMan/FLUX.2-klein-9B-Text-Encoder-Pruned-5.1B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SearchingMan/FLUX.2-klein-9B-Text-Encoder-Pruned-5.1B", torch_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
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