Instructions to use TechCarbasa/MyModels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use TechCarbasa/MyModels 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 TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: llama cli -hf TechCarbasa/MyModels:Q5_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: llama cli -hf TechCarbasa/MyModels:Q5_0
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 TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: ./llama-cli -hf TechCarbasa/MyModels:Q5_0
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 TechCarbasa/MyModels:Q5_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf TechCarbasa/MyModels:Q5_0
Use Docker
docker model run hf.co/TechCarbasa/MyModels:Q5_0
- LM Studio
- Jan
- Ollama
How to use TechCarbasa/MyModels with Ollama:
ollama run hf.co/TechCarbasa/MyModels:Q5_0
- Unsloth Desktop
- Pi
How to use TechCarbasa/MyModels with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf TechCarbasa/MyModels:Q5_0
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": "TechCarbasa/MyModels:Q5_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use TechCarbasa/MyModels with Docker Model Runner:
docker model run hf.co/TechCarbasa/MyModels:Q5_0
- Lemonade
How to use TechCarbasa/MyModels with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TechCarbasa/MyModels:Q5_0
Run and chat with the model
lemonade run user.MyModels-Q5_0
List all available models
lemonade list
- Hermes Agent
How to use TechCarbasa/MyModels with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf TechCarbasa/MyModels:Q5_0
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 TechCarbasa/MyModels:Q5_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use TechCarbasa/MyModels with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf TechCarbasa/MyModels:Q5_0
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 "TechCarbasa/MyModels:Q5_0" \ --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"
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| "class_type": "ResolutionSelector", | |
| "_meta": { | |
| "title": "Resolution Selector" | |
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| "filename_prefix": "Ideogram_4.0", | |
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| "class_type": "SaveImage", | |
| "_meta": { | |
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| "import_mode": "when empty", | |
| "output_format": "compact", | |
| "coord_mode": "normalized", | |
| "bbox_order": "yx" | |
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| "class_type": "Ideogram4PromptBuilderKJ", | |
| "_meta": { | |
| "title": "Ideogram 4 Prompt Builder KJ" | |
| } | |
| }, | |
| "296": { | |
| "inputs": { | |
| "vae_name": "split_files/vae/flux2-vae.safetensors" | |
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| "class_type": "VAELoader", | |
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| "class_type": "ConditioningZeroOut", | |
| "_meta": { | |
| "title": "Conditioning Zero Out" | |
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| "class_type": "EmptyFlux2LatentImage", | |
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| "title": "Empty Flux 2 Latent" | |
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| "class_type": "SamplerCustomAdvanced", | |
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| "title": "SamplerCustomAdvanced" | |
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| "class_type": "VAEDecode", | |
| "_meta": { | |
| "title": "VAE Decode" | |
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| "301": { | |
| "inputs": { | |
| "sampler_name": "euler" | |
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| "class_type": "KSamplerSelect", | |
| "_meta": { | |
| "title": "KSamplerSelect" | |
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| "std": [ | |
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| ] | |
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| "class_type": "Ideogram4Scheduler", | |
| "_meta": { | |
| "title": "Ideogram 4 Scheduler" | |
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| "303": { | |
| "inputs": { | |
| "noise_seed": 655607360941634 | |
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| "class_type": "RandomNoise", | |
| "_meta": { | |
| "title": "RandomNoise" | |
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| "304": { | |
| "inputs": { | |
| "unet_name": "ideogram4_fp8_scaled.safetensors", | |
| "weight_dtype": "default" | |
| }, | |
| "class_type": "UNETLoader", | |
| "_meta": { | |
| "title": "Load Diffusion Model" | |
| } | |
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| "305": { | |
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| "class_type": "CLIPTextEncode", | |
| "_meta": { | |
| "title": "CLIP Text Encode (Positive Prompt)" | |
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| "306": { | |
| "inputs": { | |
| "clip_name": "text_encoders/qwen3vl_8b_fp8_scaled.safetensors", | |
| "type": "ideogram4", | |
| "device": "default" | |
| }, | |
| "class_type": "CLIPLoader", | |
| "_meta": { | |
| "title": "Load CLIP" | |
| } | |
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| "307": { | |
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| "value": [ | |
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| "class_type": "ComfyMathExpression", | |
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| "class_type": "JsonExtractString", | |
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| "class_type": "ComfyNumberConvert", | |
| "_meta": { | |
| "title": "Convert Number" | |
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| }, | |
| "class_type": "JsonExtractString", | |
| "_meta": { | |
| "title": "Extract Text from JSON" | |
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| "key": "num_steps" | |
| }, | |
| "class_type": "JsonExtractString", | |
| "_meta": { | |
| "title": "Extract Text from JSON" | |
| } | |
| }, | |
| "317": { | |
| "inputs": { | |
| "json_string": [ | |
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| "key": "std" | |
| }, | |
| "class_type": "JsonExtractString", | |
| "_meta": { | |
| "title": "Extract Text from JSON" | |
| } | |
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| "318": { | |
| "inputs": { | |
| "value": [ | |
| "316", | |
| 0 | |
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| }, | |
| "class_type": "ComfyNumberConvert", | |
| "_meta": { | |
| "title": "Convert Number" | |
| } | |
| }, | |
| "319": { | |
| "inputs": { | |
| "unet_name": "diffusion_models/ideogram4_unconditional_fp8_scaled.safetensors", | |
| "weight_dtype": "default" | |
| }, | |
| "class_type": "UNETLoader", | |
| "_meta": { | |
| "title": "Load Diffusion Model" | |
| } | |
| }, | |
| "320": { | |
| "inputs": { | |
| "cfg": 3, | |
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| "end_percent": 1, | |
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| "class_type": "CFGOverride", | |
| "_meta": { | |
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| "321": { | |
| "inputs": { | |
| "cfg": 7, | |
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| "class_type": "DualModelGuider", | |
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| "322": { | |
| "inputs": { | |
| "choice": "Turbo", | |
| "index": 2, | |
| "option1": "Quality", | |
| "option2": "Default", | |
| "option3": "Turbo", | |
| "option4": "" | |
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| "class_type": "CustomCombo", | |
| "_meta": { | |
| "title": "Custom Combo" | |
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| } |