Instructions to use Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit 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 Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0
# Run inference directly in the terminal:
llama cli -hf Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0
# Run inference directly in the terminal:
llama cli -hf Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0

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 Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0

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 Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0

Use Docker

docker model run hf.co/Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0

LM Studio
Jan

vLLM

How to use Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0

Ollama
How to use Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit with Ollama:
```
ollama run hf.co/Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0
```
Unsloth Desktop
Docker Model Runner
How to use Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit with Docker Model Runner:
```
docker model run hf.co/Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0
```

Lemonade

How to use Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Agnuxo/gemma-2-2b-Python_CODE_assistant-GGUF_8bit:Q8_0

Run and chat with the model

lemonade run user.gemma-2-2b-Python_CODE_assistant-GGUF_8bit-Q8_0

List all available models

lemonade list

Atomic Chat

gemma-2-2b-Python_CODE_assistant-GGUF_8bit

2.78 GB

Ctrl+K

1 contributor

History: 5 commits

Agnuxo

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