Instructions to use HelloTestUser/FLUX.1-Fill-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HelloTestUser/FLUX.1-Fill-dev with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HelloTestUser/FLUX.1-Fill-dev", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use HelloTestUser/FLUX.1-Fill-dev with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| license: other | |
| license_name: flux-1-dev-non-commercial-license | |
| license_link: LICENSE.md | |
| extra_gated_prompt: By clicking "Agree", you agree to the [FluxDev Non-Commercial License Agreement](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/LICENSE.md) | |
| and acknowledge the [Acceptable Use Policy](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/POLICY.md). | |
| tags: | |
| - image-generation | |
| - flux | |
| - diffusion-single-file | |
|  | |
| `FLUX.1 Fill [dev]` is a 12 billion parameter rectified flow transformer capable of filling areas in existing images based on a text description. | |
| For more information, please read our [blog post](https://blackforestlabs.ai/flux-1-tools/). | |
| # Key Features | |
| 1. Cutting-edge output quality, second only to our state-of-the-art model `FLUX.1 Fill [pro]`. | |
| 2. Blends impressive prompt following with completing the structure of your source image. | |
| 3. Trained using guidance distillation, making `FLUX.1 Fill [dev]` more efficient. | |
| 4. Open weights to drive new scientific research, and empower artists to develop innovative workflows. | |
| 5. Generated outputs can be used for personal, scientific, and commercial purposes as described in the [`FLUX.1 [dev]` Non-Commercial License](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md). | |
| # Usage | |
| We provide a reference implementation of `FLUX.1 Fill [dev]`, 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 Fill [dev]` are encouraged to use this as a starting point. | |
| ## API Endpoints | |
| The FLUX.1 models are also available in our API [bfl.ml](https://docs.bfl.ml/) | |
|  | |
| ## Diffusers | |
| To use `FLUX.1 Fill [dev]` with the 🧨 diffusers python library, first install or upgrade diffusers | |
| ```shell | |
| pip install -U diffusers | |
| ``` | |
| Then you can use `FluxFillPipeline` to run the model | |
| ```python | |
| import torch | |
| from diffusers import FluxFillPipeline | |
| from diffusers.utils import load_image | |
| image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png") | |
| mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png") | |
| pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16).to("cuda") | |
| image = pipe( | |
| prompt="a white paper cup", | |
| image=image, | |
| mask_image=mask, | |
| height=1632, | |
| width=1232, | |
| guidance_scale=30, | |
| num_inference_steps=50, | |
| max_sequence_length=512, | |
| generator=torch.Generator("cpu").manual_seed(0) | |
| ).images[0] | |
| image.save(f"flux-fill-dev.png") | |
| ``` | |
| To learn more check out the [diffusers](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux) 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. | |
| - There may be slight-color shifts in areas that are not filled in | |
| - Filling in complex textures may produce lines at the edges of the filled-area. | |
| # 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, threat |