FLUX.1 Schnell
FLUX.1 [schnell] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post.
Modellquelle
- Art
- UNet
- Dateigröße
- 160 MB–22,1 GB
- Basismodell
- FLUX
- Version
- vRevision cb2d0f9
- Aktualisiert
- 3. Okt. 2026
- Verleger
- @lzyvegetable
- Downloads
- 1193
- Aufgaben
- Text zu Bild
- Quelle
- Hugging Face
Quellenbeschreibung
FLUX.1 [schnell] Grid
FLUX.1 [schnell] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions.
For more information, please read our blog post.
Key Features
- Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives.
- Trained using latent adversarial diffusion distillation,
FLUX.1 [schnell]can generate high-quality images in only 1 to 4 steps. - Released under the
apache-2.0licence, the model can be used for personal, scientific, and commercial purposes.
Usage
We provide a reference implementation of FLUX.1 [schnell], as well as sampling code, in a dedicated github repository.
Developers and creatives looking to build on top of FLUX.1 [schnell] are encouraged to use this as a starting point.
API Endpoints
The FLUX.1 models are also available via API from the following sources
- bfl.ml (currently
FLUX.1 [pro]) - replicate.com
- fal.ai
- mystic.ai
ComfyUI
FLUX.1 [schnell] is also available in Comfy UI for local inference with a node-based workflow.
Diffusers
To use FLUX.1 [schnell] with the 🧨 diffusers python library, first install or upgrade diffusers
pip install -U diffusers
Then you can use FluxPipeline to run the model
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
prompt = "A cat holding a sign that says hello world"
image = pipe(
prompt,
guidance_scale=0.0,
num_inference_steps=4,
max_sequence_length=256,
generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-schnell.png")
To learn more check out the diffusers documentation
Limitations
- This model is not intended or able to provide factual information.
- As a statistical model this checkpoint might amplify existing societal biases.
- The model may fail to generate output that matches the prompts.
- Prompt following is heavily influenced by the prompting-style.
Out-of-Scope Use
The model and its derivatives may not be used
- In any way that violates any applicable national, federal, state, local or international law or regulation.
- For the purpose of exploiting, harming or attempting to exploit or harm minors in any way; including but not limited to the solicitation, creation, acquisition, or dissemination of child exploitative content.
- To generate or disseminate verifiably false information and/or content with the purpose of harming others.
- To generate or disseminate personal identifiable information that can be used to harm an individual.
- To harass, abuse, threaten, stalk, or bully individuals or groups of individuals.
- To create non-consensual nudity or illegal pornographic content.
- For fully automated decision making that adversely impacts an individual's legal rights or otherwise creates or modifies a binding, enforceable obligation.
- Generating or facilitating large-scale disinformation campaigns.
Anforderungen
Modelle
2- Gefunden
VAE · 320 MB · SAFETENSORS · FP32 (tensor header) · Hugging Face · lzyvegetable/FLUX.1-schnell
vae/diffusion_pytorch_model.safetensors
Nicht aufgelöstVAE · Hugging Face · lzyvegetable/FLUX.1-schnell
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 3. Okt.
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6 Artefakte
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Quellenauszüge
3 Auszüge--- language: - en license: apache-2.0 tags: - text-to-image - image-generation - flux --- ![FLUX.1 [schnell] Grid](./schnell_grid.jpeg) `FLUX.1 [schnell]` is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our [blog post](https://blackforestlabs.ai/announcing-black-forest-labs/). # Key Features 1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives. 2. Trained using latent adversarial diffusion distillation, `FLUX.1 [schnell]` can generate high-quality images in only 1 to 4 steps. 3. Released under the `apache-2.0` licence, the model can be used for personal, scientific, and commercial purposes. # Usage We provide a reference implementation of `FLUX.1 [schnell]`, as well as sampling code, in a dedicated [github repository](https://github.com/black-forest-labs/flux). Developers and creatives looking to build on top of `FLUX.1 [schnell]` are encouraged to use this as a starting point. ## API Endpoints The FLUX.1 models are also available via API from the following sources - [bfl.ml](https://docs.bfl.ml/) (currently `FLUX.1 [pro]`) - [replicate.com](https://replicate.com/collections/flux) - [fal.ai](https://fal.ai/models/fal-ai/flux/schnell) - [mystic.ai](https://www.mystic.ai/black-forest-labs/flux1-schnell) ## ComfyUI `FLUX.1 [schnell]` is also available in [Comfy UI](https://github.com/comfyanonymous/ComfyUI) for local inference with a node-based workflow. ## Diffusers To use `FLUX.1 [schnell]` with the 🧨 diffusers python library, first install or upgrade diffusers ```shell pip install -U diffusers ``` Then you can use `FluxPipeline` to run the model ```python import torch from diffusers import FluxPipeline pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16) pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power prompt = "A cat holding a sign that says hello world" image = pipe( prompt, guidance_scale=0.0, num_inference_steps=4, max_sequence_length=256, generator=torch.Generator("cpu").manual_seed(0) ).images[0] image.save("flux-schnell.png") ``` To learn more check out the [diffusers](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux) documentation --- # L...
Source context: 1193 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo lzyvegetable/FLUX.1-schnell
Source context: 1228 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo lzyvegetable/FLUX.1-schnell
