Instructions to use Forceless/DeepPresenter-9B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Forceless/DeepPresenter-9B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Forceless/DeepPresenter-9B-GGUF",
	filename="DeepPresenter-9B-GGUF-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Forceless/DeepPresenter-9B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Forceless/DeepPresenter-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Forceless/DeepPresenter-9B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Forceless/DeepPresenter-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Forceless/DeepPresenter-9B-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 Forceless/DeepPresenter-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Forceless/DeepPresenter-9B-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 Forceless/DeepPresenter-9B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Forceless/DeepPresenter-9B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Forceless/DeepPresenter-9B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use Forceless/DeepPresenter-9B-GGUF with Ollama:
```
ollama run hf.co/Forceless/DeepPresenter-9B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use Forceless/DeepPresenter-9B-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 Forceless/DeepPresenter-9B-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 Forceless/DeepPresenter-9B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Forceless/DeepPresenter-9B-GGUF to start chatting

Pi new

How to use Forceless/DeepPresenter-9B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Forceless/DeepPresenter-9B-GGUF:Q4_K_M

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": "DeepPresenter-9B-GGUF"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Forceless/DeepPresenter-9B-GGUF with Docker Model Runner:
```
docker model run hf.co/Forceless/DeepPresenter-9B-GGUF:Q4_K_M
```

Lemonade

How to use Forceless/DeepPresenter-9B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Forceless/DeepPresenter-9B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.DeepPresenter-9B-GGUF-Q4_K_M

List all available models

lemonade list

This is a quantized version of the model for lightweight deployment on edge devices such as Macs.

DeepPresenter-9B

Project: https://github.com/icip-cas/PPTAgent
Paper: https://arxiv.org/abs/2602.22839

Model Overview

DeepPresenter-9B is a 9B-parameter language model designed for automatic presentation generation. It serves as the core model in the DeepPresenter framework, enabling agentic workflows that generate structured slide presentations from natural language instructions.

Usage

DeepPresenter-9B is intended to be used with the PPTAgent framework for full presentation generation:

uvx pptagent onboard

uvx pptagent generate "Single Page with Title: Hello World" -o hello.pptx

Performance

Downloads last month: 816

GGUF

Model size

9B params

Architecture

qwen35

Hardware compatibility

4-bit

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for Forceless/DeepPresenter-9B-GGUF

Base model

Qwen/Qwen3.5-9B-Base

Finetuned

Qwen/Qwen3.5-9B

Finetuned

Forceless/DeepPresenter-9B

Quantized

(2)

this model

Paper for Forceless/DeepPresenter-9B-GGUF

DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

Paper • 2602.22839 • Published Feb 26 • 3