Instructions to use JeloH/aisales-agent-7b-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 JeloH/aisales-agent-7b-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 JeloH/aisales-agent-7b-gguf:F16
# Run inference directly in the terminal:
llama cli -hf JeloH/aisales-agent-7b-gguf:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf JeloH/aisales-agent-7b-gguf:F16
# Run inference directly in the terminal:
llama cli -hf JeloH/aisales-agent-7b-gguf:F16

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 JeloH/aisales-agent-7b-gguf:F16
# Run inference directly in the terminal:
./llama-cli -hf JeloH/aisales-agent-7b-gguf:F16

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 JeloH/aisales-agent-7b-gguf:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf JeloH/aisales-agent-7b-gguf:F16

Use Docker

docker model run hf.co/JeloH/aisales-agent-7b-gguf:F16

LM Studio
Jan
Ollama
How to use JeloH/aisales-agent-7b-gguf with Ollama:
```
ollama run hf.co/JeloH/aisales-agent-7b-gguf:F16
```

Unsloth Studio

How to use JeloH/aisales-agent-7b-gguf 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 JeloH/aisales-agent-7b-gguf 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 JeloH/aisales-agent-7b-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for JeloH/aisales-agent-7b-gguf to start chatting

How to use JeloH/aisales-agent-7b-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JeloH/aisales-agent-7b-gguf:F16

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": "JeloH/aisales-agent-7b-gguf:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use JeloH/aisales-agent-7b-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JeloH/aisales-agent-7b-gguf:F16

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 "JeloH/aisales-agent-7b-gguf:F16" \
  --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"

Docker Model Runner
How to use JeloH/aisales-agent-7b-gguf with Docker Model Runner:
```
docker model run hf.co/JeloH/aisales-agent-7b-gguf:F16
```

Lemonade

How to use JeloH/aisales-agent-7b-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull JeloH/aisales-agent-7b-gguf:F16

Run and chat with the model

lemonade run user.aisales-agent-7b-gguf-F16

List all available models

lemonade list

Hermes Agent

How to use JeloH/aisales-agent-7b-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 JeloH/aisales-agent-7b-gguf:F16

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 JeloH/aisales-agent-7b-gguf:F16

Run Hermes

hermes

Atomic Chat

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Check out the documentation for more information.

AI Voice Sales Agent (Qwen-7B Fine-Tuned)

This model is a fine-tuned version of Qwen-7B trained on the SFT_tk-callagent-sales-synthetic-dpo dataset for sales and customer engagement tasks. It is designed to act as an AI sales agent capable of lead qualification, customer interaction, objection handling, appointment scheduling, and product recommendations.

The model is part of the AIVoiceSellAgent2 project, which integrates LLMs to build end-to-end AI voice sales agents.

Use Cases: AI sales representatives, call-center automation, CRM assistants, customer support, and voice-based business applications

Limitations: Trained primarily on synthetic data; human oversight is recommended for production and high-stakes business interactions.

Downloads last month: 5

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

16-bit

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