Instructions to use AnonymousCodeX/pprl-1-s-gguf-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AnonymousCodeX/pprl-1-s-gguf-v1 with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("AnonymousCodeX/pprl-1-s-gguf-v1", dtype="auto")

llama-cpp-python

How to use AnonymousCodeX/pprl-1-s-gguf-v1 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="AnonymousCodeX/pprl-1-s-gguf-v1",
	filename="Merged_Model-4.0B-F16.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 AnonymousCodeX/pprl-1-s-gguf-v1 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf AnonymousCodeX/pprl-1-s-gguf-v1: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 AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf AnonymousCodeX/pprl-1-s-gguf-v1: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 AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M

Use Docker

docker model run hf.co/AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M

LM Studio
Jan
Ollama
How to use AnonymousCodeX/pprl-1-s-gguf-v1 with Ollama:
```
ollama run hf.co/AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M
```

Unsloth Studio new

How to use AnonymousCodeX/pprl-1-s-gguf-v1 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 AnonymousCodeX/pprl-1-s-gguf-v1 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 AnonymousCodeX/pprl-1-s-gguf-v1 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AnonymousCodeX/pprl-1-s-gguf-v1 to start chatting

Pi new

How to use AnonymousCodeX/pprl-1-s-gguf-v1 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AnonymousCodeX/pprl-1-s-gguf-v1: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": "AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use AnonymousCodeX/pprl-1-s-gguf-v1 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AnonymousCodeX/pprl-1-s-gguf-v1: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 AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use AnonymousCodeX/pprl-1-s-gguf-v1 with Docker Model Runner:
```
docker model run hf.co/AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M
```

Lemonade

How to use AnonymousCodeX/pprl-1-s-gguf-v1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AnonymousCodeX/pprl-1-s-gguf-v1:Q4_K_M

Run and chat with the model

lemonade run user.pprl-1-s-gguf-v1-Q4_K_M

List all available models

lemonade list

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

PPRL-1-Small is an advanced language model specifically optimized for high-quality writing generation. It is finetuned from Qwen3-4B-thinking-2507 using a Online BNPO (GRPO variant) training methodology. This approach significantly enhances the model's ability to perform deep thinking, resulting in outputs with superior creativity, logical coherence, and narrative depth.

Training Procedure

Preprocessing: Used deepseek r1 0528 and deepseek v3.1 generated 10k samples of creative writing. Then sft.

SFT Fine-tuning 2: Used our own private dataset and done 2,507 steps of supervised finetuning.

RL Fine-tuning: Online BNPO alignment using unsloth with a private critic model generate critic data,then use dsv3.1 as reward model.

Hardware: single A800 80GB GPU

Training Time: Approximately 72 GPU Hours

Open-Source Contribution: The qwen3_4 Dataset

We have open-sourced a portion of the dataset used for the BNPO training phase as qwen3_4. We believe open collaboration is key to progress and invite the community to contribute to and expand this dataset to help advance the state of AI-assisted writing. You can commit to the dataset to support our work.

Uses

The model is intended for:

Creative Writing: Generating stories, poetry, scripts, and other narrative content. Long-Form Content Creation: Writing essays, articles, reports, and blog posts with strong logical flow. Content Enhancement & Rewriting: Improving the creativity and coherence of existing text.

How to Get Started with the Model

Normal transformers inference framework is all available. Use it as a normal Qwen3 2507 thinking model.

Future Work This is just the beginning. We are continuously working on training larger and more capable models. Stay tuned for more updates! If you are interested in supporting my work or hiring me for a project, please feel free to contact me via email. I will be sharing my contact details here shortly.

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Model size

4B params

Architecture

qwen3

Hardware compatibility

3-bit

4-bit

16-bit

Inference Providers NEW

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Model tree for AnonymousCodeX/pprl-1-s-gguf-v1

Base model

Qwen/Qwen3-4B-Thinking-2507

Finetuned

AnonymousCodeX/pprl-1-small

Quantized

(1)

this model