Instructions to use profullstack/tax-guy-agent-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 profullstack/tax-guy-agent-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 profullstack/tax-guy-agent-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf profullstack/tax-guy-agent-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf profullstack/tax-guy-agent-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf profullstack/tax-guy-agent-GGUF:Q8_0

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf profullstack/tax-guy-agent-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama cli -hf profullstack/tax-guy-agent-GGUF:Q8_0

Use Docker

docker model run hf.co/profullstack/tax-guy-agent-GGUF:Q8_0

Llama new
LM Studio
Jan

vLLM

How to use profullstack/tax-guy-agent-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "profullstack/tax-guy-agent-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": "profullstack/tax-guy-agent-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/profullstack/tax-guy-agent-GGUF:Q8_0

Ollama
How to use profullstack/tax-guy-agent-GGUF with Ollama:
```
ollama run hf.co/profullstack/tax-guy-agent-GGUF:Q8_0
```
Unsloth Desktop

How to use profullstack/tax-guy-agent-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf profullstack/tax-guy-agent-GGUF:Q8_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": "profullstack/tax-guy-agent-GGUF:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use profullstack/tax-guy-agent-GGUF with Docker Model Runner:
```
docker model run hf.co/profullstack/tax-guy-agent-GGUF:Q8_0
```

Lemonade

How to use profullstack/tax-guy-agent-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull profullstack/tax-guy-agent-GGUF:Q8_0

Run and chat with the model

lemonade run user.tax-guy-agent-GGUF-Q8_0

List all available models

lemonade list

Hermes Agent

How to use profullstack/tax-guy-agent-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 profullstack/tax-guy-agent-GGUF:Q8_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 profullstack/tax-guy-agent-GGUF:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use profullstack/tax-guy-agent-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf profullstack/tax-guy-agent-GGUF:Q8_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 "profullstack/tax-guy-agent-GGUF:Q8_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"

tax-guy-agent-GGUF / README.md

chovyfu

tax-guy-agent: tax-guy-agent-Q8_0.gguf

0130d97 verified 2 days ago

preview code

Raw History Blame Contribute Delete

1.47 kB

---
base_model: Qwen/Qwen2.5-0.5B-Instruct
tags: [gguf, ollama, llama.cpp, tax, taxes, accounting, tax-research, cpu, c0mpute]
license: apache-2.0
pipeline_tag: text-generation
---
# tax-guy-agent (GGUF)

> **Not a CPA. Not tax advice. Tax research from public sources; rules change every year and vary by place, so check with a CPA or enrolled agent before filing.**

[profullstack/tax-guy-agent](https://huggingface.co/profullstack/tax-guy-agent) merged into Qwen2.5-0.5B-Instruct and quantized (531 MB). Runs on a CPU.

```bash
ollama run hf.co/profullstack/tax-guy-agent-GGUF "Do I have to pay quarterly estimated taxes as a freelancer?"
```

Ollama picks up the system prompt (`system`) and sampling settings (`params`) from this repo.
llama.cpp: `llama-cli -hf profullstack/tax-guy-agent-GGUF`.

Trained on the c0mpute network: 2614 documents from rssamplifier.com topics and pit.world search, 400 LoRA steps (r=8), held-out perplexity 33.6 to 17.8. Adapter sha256 `821a038ac1ea43f804b795e795a308cfbebb141c24e3675223c29d80fb8db5b7` (matches the c0mpute receipt).
Every Infernet and c0mpute node pulls this model automatically ([house models](https://infernetprotocol.com/docs/house-models)).
It answers best with fresh search results in the prompt (`w3bs ask`, or the example's `chat.py`); a 0.5B model supplies the voice, not the facts.

Built with the [c0mpute example](https://github.com/profullstack/c0mpute/tree/master/examples/business-strategist-agent).

	---
	base_model: Qwen/Qwen2.5-0.5B-Instruct
	tags: [gguf, ollama, llama.cpp, tax, taxes, accounting, tax-research, cpu, c0mpute]
	license: apache-2.0
	pipeline_tag: text-generation
	---

	# tax-guy-agent (GGUF)

	> Not a CPA. Not tax advice. Tax research from public sources; rules change every year and vary by place, so check with a CPA or enrolled agent before filing.

	[profullstack/tax-guy-agent](https://huggingface.co/profullstack/tax-guy-agent) merged into Qwen2.5-0.5B-Instruct and quantized (531 MB). Runs on a CPU.

	```bash
	ollama run hf.co/profullstack/tax-guy-agent-GGUF "Do I have to pay quarterly estimated taxes as a freelancer?"
	```

	Ollama picks up the system prompt (`system`) and sampling settings (`params`) from this repo.
	llama.cpp: `llama-cli -hf profullstack/tax-guy-agent-GGUF`.

	Trained on the c0mpute network: 2614 documents from rssamplifier.com topics and pit.world search, 400 LoRA steps (r=8), held-out perplexity 33.6 to 17.8. Adapter sha256 `821a038ac1ea43f804b795e795a308cfbebb141c24e3675223c29d80fb8db5b7` (matches the c0mpute receipt).
	Every Infernet and c0mpute node pulls this model automatically ([house models](https://infernetprotocol.com/docs/house-models)).
	It answers best with fresh search results in the prompt (`w3bs ask`, or the example's `chat.py`); a 0.5B model supplies the voice, not the facts.

	Built with the [c0mpute example](https://github.com/profullstack/c0mpute/tree/master/examples/business-strategist-agent).