Instructions to use mhnakif/comfy2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mhnakif/comfy2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mhnakif/comfy2", 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
Ctrl+K
- FlashVSR
- audio_encoders
- background_removal
- checkpoints
- clip
- clip_seg
- clip_vision
- configs
- controlnet
- detection
- diffusers
- diffusion_models
- embeddings
- frame_interpolation
- geometry_estimation
- gligen
- hypernetworks
- latent_upscale_models
- model_patches
- optical_flow
- photomaker
- style_models
- text_encoders
- unet
- upscale_models
- vae
- vae_approx