Create README.md

README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- text-to-image
+- image-generation
+- flux
+---
+# FLUX.1 [schnell] 
+
+> **Note:** This is an **archived / mirror repository**, **not** the original upstream source.  
+> All official updates, releases, and maintenance are handled by **Black Forest Labs**.
+
+`FLUX.1 [schnell]` is a 12-billion-parameter rectified flow transformer capable of generating high-quality images from text descriptions.
+
+**Official Announcement:**  
+🔗 https://blackforestlabs.ai/announcing-black-forest-labs/
+
+## Official Upstream Sources
+
+- **FLUX.1-schnell — black-forest-labs (original Hugging Face model)**  
+  https://huggingface.co/black-forest-labs/FLUX.1-schnell
+
+# 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
+
+A full reference implementation of `FLUX.1 [schnell]`, including sampling code, is available in the official GitHub repository:
+  https://github.com/black-forest-labs/flux
+
+Developers and creators should rely on the upstream GitHub repository when building applications, tools, or fine-tuning pipelines.
+
+## 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
+
+---
+# 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.