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add diffusers weights (#4)
- add diffusers weights (03216e1d673120f9467575e1e84ff1ff21f2c29f) Co-authored-by: YiYi Xu <YiYiXu@users.noreply.huggingface.co>
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ai-modelscope
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README.md
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README.md
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---
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license: Apache License 2.0
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#model-type:
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##如 gpt、phi、llama、chatglm、baichuan 等
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#- gpt
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#domain:
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##如 nlp、cv、audio、multi-modal
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#- nlp
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#language:
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##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
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#- cn
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#metrics:
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##如 CIDEr、Blue、ROUGE 等
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#- CIDEr
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#tags:
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##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
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#- pretrained
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#tools:
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##如 vllm、fastchat、llamacpp、AdaSeq 等
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#- vllm
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language:
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- en
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license: other
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license_name: flux-1-dev-non-commercial-license
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license_link: LICENSE.md
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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)
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and acknowledge the [Acceptable Use Policy](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/POLICY.md).
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tags:
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- image-generation
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- flux
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- diffusion-single-file
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---
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### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。
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#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型
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SDK下载
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```bash
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#安装ModelScope
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pip install modelscope
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`FLUX.1 Fill [dev]` is a 12 billion parameter rectified flow transformer capable of filling areas in existing images based on a text description.
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For more information, please read our [blog post](https://blackforestlabs.ai/flux-1-tools/).
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# Key Features
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1. Cutting-edge output quality, second only to our state-of-the-art model `FLUX.1 Fill [pro]`.
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2. Blends impressive prompt following with completing the structure of your source image.
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3. Trained using guidance distillation, making `FLUX.1 Fill [dev]` more efficient.
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4. Open weights to drive new scientific research, and empower artists to develop innovative workflows.
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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).
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# Usage
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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).
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Developers and creatives looking to build on top of `FLUX.1 Fill [dev]` are encouraged to use this as a starting point.
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## API Endpoints
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The FLUX.1 models are also available in our API [bfl.ml](https://docs.bfl.ml/)
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## Diffusers
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To use `FLUX.1 Fill [dev]` with the 🧨 diffusers python library, first install or upgrade diffusers
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```shell
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pip install -U diffusers
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```
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Then you can use `FluxFillPipeline` to run the model
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```python
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#SDK模型下载
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from modelscope import snapshot_download
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model_dir = snapshot_download('black-forest-labs/FLUX.1-Fill-dev')
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```
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Git下载
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```
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#Git模型下载
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git clone https://www.modelscope.cn/black-forest-labs/FLUX.1-Fill-dev.git
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import torch
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from diffusers import FluxFillPipeline
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from diffusers.utils import load_image
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image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
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mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")
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pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16).to("cuda")
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image = pipe(
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prompt="a white paper cup",
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image=image,
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mask_image=mask,
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height=1632,
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width=1232,
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guidance_scale=30,
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num_inference_steps=50,
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max_sequence_length=512,
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generator=torch.Generator("cpu").manual_seed(0)
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).images[0]
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image.save(f"flux-fill-dev.png")
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```
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<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>，及时完善模型卡片内容。</p>
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To learn more check out the [diffusers](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux) documentation
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---
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# Limitations
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- This model is not intended or able to provide factual information.
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- As a statistical model this checkpoint might amplify existing societal biases.
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- The model may fail to generate output that matches the prompts.
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- Prompt following is heavily influenced by the prompting-style.
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- There may be slight-color shifts in areas that are not filled in
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- Filling in complex textures may produce lines at the edges of the filled-area.
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# Out-of-Scope Use
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The model and its derivatives may not be used
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- In any way that violates any applicable national, federal, state, local or international law or regulation.
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- 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.
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- To generate or disseminate verifiably false information and/or content with the purpose of harming others.
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- To generate or disseminate personal identifiable information that can be used to harm an individual.
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- To harass, abuse, threat
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