Instructions to use BAAI/nova-d48w1024-sd512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BAAI/nova-d48w1024-sd512 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BAAI/nova-d48w1024-sd512", 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 Settings
- Draw Things
- DiffusionBee
Update model type
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README.md
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## Model Details
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- **Developed by:** BAAI
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- **Model type:**
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- **Model size:** 645M
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- **Model precision:** torch.float16 (FP16)
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- **Model resolution:** 512x512
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- **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [
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- **Model License:** [Apache 2.0 License](LICENSE)
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- **Resources for more information:** [GitHub Repository](https://github.com/baaivision/NOVA).
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## Model Details
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- **Developed by:** BAAI
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- **Model type:** Non-quantized Autoregressive Text-to-Image Generation Model
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- **Model size:** 645M
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- **Model precision:** torch.float16 (FP16)
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- **Model resolution:** 512x512
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- **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Non-quantized Video Autoregressive (NOVA)](https://arxiv.org/abs/2412.14169) diffusion model that uses a pretrained text encoder ([Phi-2](https://huggingface.co/microsoft/phi-2)) and one VAE image tokenizer ([SD-VAE](https://huggingface.co/stabilityai/sd-vae-ft-mse)).
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- **Model License:** [Apache 2.0 License](LICENSE)
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- **Resources for more information:** [GitHub Repository](https://github.com/baaivision/NOVA).
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