| | --- |
| | license: agpl-3.0 |
| | language: |
| | - zh |
| | - en |
| | |
| | |
| | |
| | |
| | tags: |
| | - flux |
| | - lora |
| | - china |
| | - girl |
| | - flux-diffusers |
| | - text-to-image |
| | - diffusers |
| | thumbnail: ./1758914667.5504615.png |
| | widget: |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758914667.5504615.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758914240.346111.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758914165.4060624.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758912371.6772127.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758912781.4197416.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758913508.8816087.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758916370.734687.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758912529.5807238.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758912853.6719186.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758913581.5424395.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758912627.3229315.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758912932.3310673.png |
| | - text: 'none' |
| | parameters: |
| | negative_prompt: 'none' |
| | output: |
| | url: ./1758915800.3715427.png |
| | --- |
| | |
| | # Pandora |
| |
|
| | <img src="https://cdn-uploads.huggingface.co/production/uploads/66719e03a4dd9ce916a82688/kGCLjdcFmTfNFTTbQfah7.png" width="50%" /> |
| |
|
| | A model for generating realistic, high-quality images captured on a mobile phone. |
| |
|
| | It uses a two-stage training process: the first stage uses a low-quality dataset to help the model learn outlines, and the second stage uses a high-quality dataset to improve image quality and details. |
| |
|
| | Every image generated will surprise you. |
| |
|
| | --- |
| |
|
| | I've enabled gate access. |
| |
|
| | You can submit an access request, which I will manually review. |
| |
|
| | If you would like to expedite the process, please pay me $100, and I will then grant you access. |
| |
|
| | For payment-related questions, you should email me. |
| |
|
| | daylog@qq.com |
| |
|
| | --- |
| |
|
| | <Gallery /> |
| |
|
| | ## Use |
| |
|
| | Using a custom pipeline for inference yields the best performance |
| |
|
| | ```python |
| | import torch |
| | from diffusers import FluxPipeline |
| | |
| | base_model = "black-forest-labs/FLUX.1-dev" |
| | repo = "likewendy/pandora" |
| | |
| | pipe = DiffusionPipeline.from_pretrained( |
| | base_model, |
| | custom_pipeline=repo, |
| | trust_remote_code=True, |
| | torch_dtype=torch.bfloat16 |
| | ) |
| | |
| | pipe.load_lora_weights(repo) |
| | pipe.enable_model_cpu_offload() |
| | |
| | img = pipe( |
| | prompt="1 gril", |
| | negative_prompt="low quality, deformed, watermark", |
| | height=1024, |
| | width=1024, |
| | guidance_scale=3.2, |
| | num_inference_steps=36, |
| | generator=torch.Generator(device=pipe.device).manual_seed(42) |
| | ).images[0] |
| | |
| | img.save("out.png") |
| | ``` |
| |
|
| | ## Limitations |
| | - This model is not intended to or capable of providing factual information. |
| | - As a statistical model, this checkpoint may amplify existing social biases. |
| | - The model may not generate output that matches the prompt. |
| | - Tip following is significantly influenced by the prompt style. |
| |
|
| | ## Out-of-scope Use |
| | This model and its derivatives may not be used |
| | - in any manner 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 soliciting, creating, acquiring, or distributing child exploitation content. |
| | - Creating or disseminating verifiably false information and/or content with the intent to harm others. |
| | - Creating or disseminating personally identifiable information that could be used to harm individuals. |
| | - Harassing, abusing, threatening, stalking, or bullying individuals or groups. |
| | - Creating non-consensual nudity or illegal pornography. |
| | - For fully automated decision-making, adversely affecting the legal rights of individuals or otherwise creating or modifying binding, enforceable obligations. |
| | - Initiating or facilitating large-scale disinformation campaigns. |
| |
|
| | ## Responsible Artificial Intelligence |
| |
|
| | I am committed to the responsible development of generative AI technology. |
| | - Before releasing Pandora, I evaluated and mitigated numerous risks in the Pandora model and service, including the generation of illegal content. |
| | - I implemented a series of pre-release mitigations to help prevent third-party misuse. |
| | - For example, the HuggingFace repository for the Pandora model includes inference filters for illegal or infringing content. |
| | - Use of the model must comply with the terms of the Pandora license and be subject to filters or human review. |
| | - We may randomly contact known deployers of the Pandora model to verify that filters or human review processes are in place. |