Text-to-Image
Diffusers
English
Text-to-Image
IP-Adapter
StableDiffusion3Pipeline
image-generation
Stable Diffusion
Instructions to use guiyrt/InstantX-SD3.5-Large-IP-Adapter-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use guiyrt/InstantX-SD3.5-Large-IP-Adapter-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("guiyrt/InstantX-SD3.5-Large-IP-Adapter-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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# SD3.5-Large-IP-Adapter
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This repository contains the checkpoints for the diffusers implementation of [InstantX/SD3.5-Large-IP-Adapter](https://huggingface.co/InstantX/SD3.5-Large-IP-Adapter)
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# Model Card
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This is a regular IP-Adapter, where the new layers are added into all 38 blocks. We use [google/siglip-so400m-patch14-384](https://huggingface.co/google/siglip-so400m-patch14-384) to encode image for its superior performance, and adopt a TimeResampler to project. The image token number is set to 64.
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# SD3.5-Large-IP-Adapter
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This repository contains the checkpoints for with updated key names for the diffusers implementation of [InstantX/SD3.5-Large-IP-Adapter](https://huggingface.co/InstantX/SD3.5-Large-IP-Adapter).
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As there is now runtime convertion implemented, you can just use [InstantX/SD3.5-Large-IP-Adapter](https://huggingface.co/InstantX/SD3.5-Large-IP-Adapter).
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It's an IP-Adapter for SD3.5-Large model released by researchers from [InstantX Team](https://huggingface.co/InstantX), where image work just like text, so it may not be responsive or interfere with other text, but we do hope you enjoy this model, have fun and share your creative works with us [on Twitter](https://x.com/instantx_ai).
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# Model Card
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This is a regular IP-Adapter, where the new layers are added into all 38 blocks. We use [google/siglip-so400m-patch14-384](https://huggingface.co/google/siglip-so400m-patch14-384) to encode image for its superior performance, and adopt a TimeResampler to project. The image token number is set to 64.
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