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 Studio
How to use TechCarbasa/MyModels 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 TechCarbasa/MyModels 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 TechCarbasa/MyModels to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for TechCarbasa/MyModels to start chatting
- 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 @mariozechner/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"
Upload workflows/image_ideogram4_V1 with KJ Prompt BuilderAPI.json
Browse files
workflows/image_ideogram4_V1 with KJ Prompt BuilderAPI.json
ADDED
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|
| 1 |
+
{
|
| 2 |
+
"37": {
|
| 3 |
+
"inputs": {
|
| 4 |
+
"aspect_ratio": "9:16 (Portrait Widescreen)",
|
| 5 |
+
"megapixels": 1,
|
| 6 |
+
"multiple": 8
|
| 7 |
+
},
|
| 8 |
+
"class_type": "ResolutionSelector",
|
| 9 |
+
"_meta": {
|
| 10 |
+
"title": "Resolution Selector"
|
| 11 |
+
}
|
| 12 |
+
},
|
| 13 |
+
"158": {
|
| 14 |
+
"inputs": {
|
| 15 |
+
"filename_prefix": "Ideogram_4.0",
|
| 16 |
+
"images": [
|
| 17 |
+
"300",
|
| 18 |
+
0
|
| 19 |
+
]
|
| 20 |
+
},
|
| 21 |
+
"class_type": "SaveImage",
|
| 22 |
+
"_meta": {
|
| 23 |
+
"title": "Save Image"
|
| 24 |
+
}
|
| 25 |
+
},
|
| 26 |
+
"267": {
|
| 27 |
+
"inputs": {
|
| 28 |
+
"width": [
|
| 29 |
+
"307",
|
| 30 |
+
0
|
| 31 |
+
],
|
| 32 |
+
"height": [
|
| 33 |
+
"308",
|
| 34 |
+
0
|
| 35 |
+
],
|
| 36 |
+
"high_level_description": "INPUTPROMPT",
|
| 37 |
+
"background": "",
|
| 38 |
+
"style": "photo",
|
| 39 |
+
"style.photo": "Realsitic",
|
| 40 |
+
"aesthetics": "",
|
| 41 |
+
"lighting": "realistic",
|
| 42 |
+
"medium": "",
|
| 43 |
+
"style_palette_data": "",
|
| 44 |
+
"elements_data": "",
|
| 45 |
+
"bg_brightness": 51,
|
| 46 |
+
"import_mode": "when empty",
|
| 47 |
+
"output_format": "compact",
|
| 48 |
+
"coord_mode": "normalized",
|
| 49 |
+
"bbox_order": "yx"
|
| 50 |
+
},
|
| 51 |
+
"class_type": "Ideogram4PromptBuilderKJ",
|
| 52 |
+
"_meta": {
|
| 53 |
+
"title": "Ideogram 4 Prompt Builder KJ"
|
| 54 |
+
}
|
| 55 |
+
},
|
| 56 |
+
"296": {
|
| 57 |
+
"inputs": {
|
| 58 |
+
"vae_name": "split_files/vae/flux2-vae.safetensors"
|
| 59 |
+
},
|
| 60 |
+
"class_type": "VAELoader",
|
| 61 |
+
"_meta": {
|
| 62 |
+
"title": "Load VAE"
|
| 63 |
+
}
|
| 64 |
+
},
|
| 65 |
+
"297": {
|
| 66 |
+
"inputs": {
|
| 67 |
+
"conditioning": [
|
| 68 |
+
"305",
|
| 69 |
+
0
|
| 70 |
+
]
|
| 71 |
+
},
|
| 72 |
+
"class_type": "ConditioningZeroOut",
|
| 73 |
+
"_meta": {
|
| 74 |
+
"title": "Conditioning Zero Out"
|
| 75 |
+
}
|
| 76 |
+
},
|
| 77 |
+
"298": {
|
| 78 |
+
"inputs": {
|
| 79 |
+
"width": [
|
| 80 |
+
"309",
|
| 81 |
+
1
|
| 82 |
+
],
|
| 83 |
+
"height": [
|
| 84 |
+
"310",
|
| 85 |
+
1
|
| 86 |
+
],
|
| 87 |
+
"batch_size": 1
|
| 88 |
+
},
|
| 89 |
+
"class_type": "EmptyFlux2LatentImage",
|
| 90 |
+
"_meta": {
|
| 91 |
+
"title": "Empty Flux 2 Latent"
|
| 92 |
+
}
|
| 93 |
+
},
|
| 94 |
+
"299": {
|
| 95 |
+
"inputs": {
|
| 96 |
+
"noise": [
|
| 97 |
+
"303",
|
| 98 |
+
0
|
| 99 |
+
],
|
| 100 |
+
"guider": [
|
| 101 |
+
"321",
|
| 102 |
+
0
|
| 103 |
+
],
|
| 104 |
+
"sampler": [
|
| 105 |
+
"301",
|
| 106 |
+
0
|
| 107 |
+
],
|
| 108 |
+
"sigmas": [
|
| 109 |
+
"302",
|
| 110 |
+
0
|
| 111 |
+
],
|
| 112 |
+
"latent_image": [
|
| 113 |
+
"298",
|
| 114 |
+
0
|
| 115 |
+
]
|
| 116 |
+
},
|
| 117 |
+
"class_type": "SamplerCustomAdvanced",
|
| 118 |
+
"_meta": {
|
| 119 |
+
"title": "SamplerCustomAdvanced"
|
| 120 |
+
}
|
| 121 |
+
},
|
| 122 |
+
"300": {
|
| 123 |
+
"inputs": {
|
| 124 |
+
"samples": [
|
| 125 |
+
"299",
|
| 126 |
+
0
|
| 127 |
+
],
|
| 128 |
+
"vae": [
|
| 129 |
+
"296",
|
| 130 |
+
0
|
| 131 |
+
]
|
| 132 |
+
},
|
| 133 |
+
"class_type": "VAEDecode",
|
| 134 |
+
"_meta": {
|
| 135 |
+
"title": "VAE Decode"
|
| 136 |
+
}
|
| 137 |
+
},
|
| 138 |
+
"301": {
|
| 139 |
+
"inputs": {
|
| 140 |
+
"sampler_name": "euler"
|
| 141 |
+
},
|
| 142 |
+
"class_type": "KSamplerSelect",
|
| 143 |
+
"_meta": {
|
| 144 |
+
"title": "KSamplerSelect"
|
| 145 |
+
}
|
| 146 |
+
},
|
| 147 |
+
"302": {
|
| 148 |
+
"inputs": {
|
| 149 |
+
"steps": [
|
| 150 |
+
"318",
|
| 151 |
+
1
|
| 152 |
+
],
|
| 153 |
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