Instructions to use Shinewonder/models-moved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shinewonder/models-moved with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Shinewonder/models-moved", 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
- Local Apps Settings
- llama.cpp
How to use Shinewonder/models-moved 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 Shinewonder/models-moved:Q4_K_M # Run inference directly in the terminal: llama cli -hf Shinewonder/models-moved:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Shinewonder/models-moved:Q4_K_M # Run inference directly in the terminal: llama cli -hf Shinewonder/models-moved:Q4_K_M
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 Shinewonder/models-moved:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Shinewonder/models-moved:Q4_K_M
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 Shinewonder/models-moved:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Shinewonder/models-moved:Q4_K_M
Use Docker
docker model run hf.co/Shinewonder/models-moved:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use Shinewonder/models-moved with Ollama:
ollama run hf.co/Shinewonder/models-moved:Q4_K_M
- Unsloth Desktop
- Pi
How to use Shinewonder/models-moved with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Shinewonder/models-moved:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Shinewonder/models-moved:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Shinewonder/models-moved with Docker Model Runner:
docker model run hf.co/Shinewonder/models-moved:Q4_K_M
- Lemonade
How to use Shinewonder/models-moved with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Shinewonder/models-moved:Q4_K_M
Run and chat with the model
lemonade run user.models-moved-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use Shinewonder/models-moved with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Shinewonder/models-moved:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Shinewonder/models-moved:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Shinewonder/models-moved with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Shinewonder/models-moved:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Shinewonder/models-moved:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Upload TencentARC/Pixal3D-T/ckpts/shape_dec_next_dc_f16c32_fp16.json with huggingface_hub
Browse files
TencentARC/Pixal3D-T/ckpts/shape_dec_next_dc_f16c32_fp16.json
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"name": "FlexiDualGridVaeDecoder",
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"model_channels": [1024, 512, 256, 128, 64],
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"latent_channels": 32,
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"num_blocks": [4, 16, 8, 4, 0],
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"SparseConvNeXtBlock3d",
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"block_args": [{}, {}, {}, {}, {}],
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}
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