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", torch_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
| license: mit | |
| datasets: | |
| - NovaSky-AI/Sky-T1_data_17k | |
| language: | |
| - en | |
| metrics: | |
| - character | |
| base_model: | |
| - deepseek-ai/DeepSeek-V3-Base | |
| new_version: deepseek-ai/DeepSeek-V3-Base | |
| pipeline_tag: text-to-audio | |
| library_name: diffusers | |
| tags: | |
| - binaural | |