Instructions to use freenetcoder/binudog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use freenetcoder/binudog with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("freenetcoder/binudog", 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
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license: mit
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---
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license: mit
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datasets:
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- NovaSky-AI/Sky-T1_data_17k
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language:
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- en
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metrics:
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- character
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base_model:
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- deepseek-ai/DeepSeek-R1
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new_version: deepseek-ai/DeepSeek-V3-Base
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pipeline_tag: text-to-audio
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library_name: diffusers
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tags:
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- binaural
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---
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