Instructions to use WithinUsAI/WithIn-Us-Coder-4B.gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WithinUsAI/WithIn-Us-Coder-4B.gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="WithinUsAI/WithIn-Us-Coder-4B.gguf",
	filename="WithIn-Us-Coder-4B.Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use WithinUsAI/WithIn-Us-Coder-4B.gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf WithinUsAI/WithIn-Us-Coder-4B.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 WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf WithinUsAI/WithIn-Us-Coder-4B.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 WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf WithinUsAI/WithIn-Us-Coder-4B.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 WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M

Use Docker

docker model run hf.co/WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use WithinUsAI/WithIn-Us-Coder-4B.gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WithinUsAI/WithIn-Us-Coder-4B.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": "WithinUsAI/WithIn-Us-Coder-4B.gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M

Ollama
How to use WithinUsAI/WithIn-Us-Coder-4B.gguf with Ollama:
```
ollama run hf.co/WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M
```

Unsloth Studio new

How to use WithinUsAI/WithIn-Us-Coder-4B.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 WithinUsAI/WithIn-Us-Coder-4B.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 WithinUsAI/WithIn-Us-Coder-4B.gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for WithinUsAI/WithIn-Us-Coder-4B.gguf to start chatting

Pi new

How to use WithinUsAI/WithIn-Us-Coder-4B.gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf WithinUsAI/WithIn-Us-Coder-4B.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": "WithIn-Us-Coder-4B.gguf"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use WithinUsAI/WithIn-Us-Coder-4B.gguf with Docker Model Runner:
```
docker model run hf.co/WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M
```

Lemonade

How to use WithinUsAI/WithIn-Us-Coder-4B.gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull WithinUsAI/WithIn-Us-Coder-4B.gguf:Q4_K_M

Run and chat with the model

lemonade run user.WithIn-Us-Coder-4B.gguf-Q4_K_M

List all available models

lemonade list

gss1147 commited on 3 days ago

Commit

18bbb52

verified ·

1 Parent(s): 29c5663

Update README.md

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README.md +19 -18

README.md CHANGED Viewed

@@ -1,28 +1,29 @@
 ---
 license: other
 base_model:
-  - Qwen/Qwen3.5-4B
 library_name: llama.cpp
 tags:
-  - gguf
-  - qwen
-  - qwen3.5
-  - code
-  - coder
-  - conversational
-  - text-generation
-  - withinusai
 language:
-  - en
 datasets:
-  - WithinUsAI/Python_GOD_Coder_50k
-  - reedmayhew/gemini-3.1-pro-2048-reasoning-1100x
-  - m-a-p/Code-Feedback
-  - crownelius/Opus-4.6-Reasoning-2100x-formatted
-  - crownelius/Opus4.6-No-Reasoning-260x
-  - crownelius/Creative_Writing_Multiturn_Enhanced
-  - HuggingFaceH4/llava-instruct-mix-vsft
-  - Roman1111111/gemini-3-pro-10000x-hard-high-reasoning
 model_type: gguf
 inference: false
 ---

 ---
 license: other
 base_model:
+- Qwen/Qwen3.5-4B
 library_name: llama.cpp
 tags:
+- gguf
+- qwen
+- qwen3.5
+- code
+- coder
+- conversational
+- text-generation
+- withinusai
 language:
+- en
 datasets:
+- WithinUsAI/Python_GOD_Coder_50k
+- reedmayhew/gemini-3.1-pro-2048-reasoning-1100x
+- m-a-p/Code-Feedback
+- crownelius/Opus-4.6-Reasoning-2100x-formatted
+- crownelius/Opus4.6-No-Reasoning-260x
+- crownelius/Creative_Writing_Multiturn_Enhanced
+- HuggingFaceH4/llava-instruct-mix-vsft
+- Roman1111111/gemini-3-pro-10000x-hard-high-reasoning
+- TeichAI/Pony-Alpha-15k
 model_type: gguf
 inference: false
 ---