Instructions to use aka7774/comfyui-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aka7774/comfyui-models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aka7774/comfyui-models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - llama-cpp-python
How to use aka7774/comfyui-models with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="aka7774/comfyui-models", filename="SEEDVR2/seedvr2_ema_7b-Q4_K_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use aka7774/comfyui-models with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf aka7774/comfyui-models:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf aka7774/comfyui-models:UD-Q4_K_XL
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf aka7774/comfyui-models:UD-Q4_K_XL
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf aka7774/comfyui-models:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf aka7774/comfyui-models:UD-Q4_K_XL
Use Docker
docker model run hf.co/aka7774/comfyui-models:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use aka7774/comfyui-models with Ollama:
ollama run hf.co/aka7774/comfyui-models:UD-Q4_K_XL
- Unsloth Studio
How to use aka7774/comfyui-models with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for aka7774/comfyui-models to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for aka7774/comfyui-models to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for aka7774/comfyui-models to start chatting
- Atomic Chat new
- Docker Model Runner
How to use aka7774/comfyui-models with Docker Model Runner:
docker model run hf.co/aka7774/comfyui-models:UD-Q4_K_XL
- Lemonade
How to use aka7774/comfyui-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull aka7774/comfyui-models:UD-Q4_K_XL
Run and chat with the model
lemonade run user.comfyui-models-UD-Q4_K_XL
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files
controlnet/config_promax.json
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{
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"_class_name": "ControlNetModel",
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"_diffusers_version": "0.20.0.dev0",
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"act_fn": "silu",
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"addition_embed_type": "text_time",
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"addition_embed_type_num_heads": 64,
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"addition_time_embed_dim": 256,
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"attention_head_dim": [
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],
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"block_out_channels": [
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320,
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1280
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],
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"class_embed_type": null,
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"conditioning_channels": 3,
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"conditioning_embedding_out_channels": [
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],
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"controlnet_conditioning_channel_order": "rgb",
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"cross_attention_dim": 2048,
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"down_block_types": [
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"DownBlock2D",
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"CrossAttnDownBlock2D",
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"CrossAttnDownBlock2D"
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],
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"downsample_padding": 1,
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"encoder_hid_dim": null,
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"encoder_hid_dim_type": null,
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"flip_sin_to_cos": true,
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"freq_shift": 0,
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"global_pool_conditions": false,
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"in_channels": 4,
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"layers_per_block": 2,
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"mid_block_scale_factor": 1,
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"norm_eps": 1e-05,
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"norm_num_groups": 32,
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"num_attention_heads": null,
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"num_class_embeds": null,
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"only_cross_attention": false,
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"projection_class_embeddings_input_dim": 2816,
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"resnet_time_scale_shift": "default",
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"transformer_layers_per_block": [
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1,
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],
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"upcast_attention": null,
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"use_linear_projection": true,
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"num_control_type": 8
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}
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controlnet/diffusers_xl_recolor_testXL-fp16.safetensors
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version https://git-lfs.github.com/spec/v1
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size 2502139104
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controlnet/diffusion_pytorch_model_promax.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9fae2e50cb431bfcbe05822b59ec2228df545ef27f711dea8949e9f4ed9f7cdc
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size 2513342408
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controlnet/put_controlnets_and_t2i_here
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