Instructions to use Flexan/DoodDood-TOMAGPT-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Flexan/DoodDood-TOMAGPT-GGUF 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 Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Flexan/DoodDood-TOMAGPT-GGUF: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 Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Flexan/DoodDood-TOMAGPT-GGUF: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 Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Flexan/DoodDood-TOMAGPT-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Flexan/DoodDood-TOMAGPT-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Flexan/DoodDood-TOMAGPT-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M

Ollama
How to use Flexan/DoodDood-TOMAGPT-GGUF with Ollama:
```
ollama run hf.co/Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M
```
Unsloth Desktop

How to use Flexan/DoodDood-TOMAGPT-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Flexan/DoodDood-TOMAGPT-GGUF: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": "Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Flexan/DoodDood-TOMAGPT-GGUF with Docker Model Runner:
```
docker model run hf.co/Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M
```

Lemonade

How to use Flexan/DoodDood-TOMAGPT-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.DoodDood-TOMAGPT-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Flexan/DoodDood-TOMAGPT-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Flexan/DoodDood-TOMAGPT-GGUF: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 Flexan/DoodDood-TOMAGPT-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Flexan/DoodDood-TOMAGPT-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Flexan/DoodDood-TOMAGPT-GGUF: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 "Flexan/DoodDood-TOMAGPT-GGUF: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"

Flexan commited on Feb 24

Commit

2b2cc52

verified ·

1 Parent(s): 225289f

Upload folder using huggingface_hub

Browse files

Files changed (12) hide show

.gitattributes +10 -0
README.md +10 -3
TOMAGPT.IQ3_M.gguf +3 -0
TOMAGPT.IQ3_S.gguf +3 -0
TOMAGPT.IQ4_XS.gguf +3 -0
TOMAGPT.Q3_K_L.gguf +3 -0
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README.md CHANGED Viewed

@@ -31,16 +31,23 @@ model-index:
 # GGUF Files for TOMAGPT
 These are the GGUF files for [DoodDood/TOMAGPT](https://huggingface.co/DoodDood/TOMAGPT).
-> [!NOTE]
-> **Note:** this model has only been quantized to **Q2_K**, **Q4_K_M**, and **Q8_0**. Other quantizations may become available later.
 ## Downloads
 | GGUF Link | Quantization | Description |
 | ---- | ----- | ----------- |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q2_K.gguf) | Q2_K | Lowest quality |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q4_K_M.gguf) | Q4_K_M | **Recommended:** Perfect mix of speed and performance |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q8_0.gguf) | Q8_0 | Best quality |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.f16.gguf) | f16 | Full precision, don't bother; use a quant |

 # GGUF Files for TOMAGPT
 These are the GGUF files for [DoodDood/TOMAGPT](https://huggingface.co/DoodDood/TOMAGPT).
 ## Downloads
 | GGUF Link | Quantization | Description |
 | ---- | ----- | ----------- |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q2_K.gguf) | Q2_K | Lowest quality |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q3_K_S.gguf) | Q3_K_S |  |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.IQ3_S.gguf) | IQ3_S | Integer quant, preferable over Q3_K_S |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.IQ3_M.gguf) | IQ3_M | Integer quant |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q3_K_M.gguf) | Q3_K_M |  |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q3_K_L.gguf) | Q3_K_L |  |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.IQ4_XS.gguf) | IQ4_XS | Integer quant |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q4_K_S.gguf) | Q4_K_S | Fast with good performance |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q4_K_M.gguf) | Q4_K_M | **Recommended:** Perfect mix of speed and performance |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q5_K_S.gguf) | Q5_K_S |  |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q5_K_M.gguf) | Q5_K_M |  |
+| [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q6_K.gguf) | Q6_K | Very good quality |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.Q8_0.gguf) | Q8_0 | Best quality |
 | [Download](https://huggingface.co/Flexan/DoodDood-TOMAGPT-GGUF/resolve/main/TOMAGPT.f16.gguf) | f16 | Full precision, don't bother; use a quant |

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