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
metadata
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