Text Generation
GGUF
Safetensors
English
Turkish
plc
iec-61131-3
structured-text
code-generation
ollama
mikrodev
ALB
AdvanceLogicBuilder
MikrodevLogicStudio
advance-logic-builder
mikrodev-logicstudio
gemma
conversational
Instructions to use Mikrodev/stcoder-gemma4-12b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Mikrodev/stcoder-gemma4-12b-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 Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf Mikrodev/stcoder-gemma4-12b-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 Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Mikrodev/stcoder-gemma4-12b-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 Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M
Use Docker
docker model run hf.co/Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Mikrodev/stcoder-gemma4-12b-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mikrodev/stcoder-gemma4-12b-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": "Mikrodev/stcoder-gemma4-12b-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M
- Ollama
How to use Mikrodev/stcoder-gemma4-12b-gguf with Ollama:
ollama run hf.co/Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M
- Unsloth Studio
How to use Mikrodev/stcoder-gemma4-12b-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 Mikrodev/stcoder-gemma4-12b-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 Mikrodev/stcoder-gemma4-12b-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Mikrodev/stcoder-gemma4-12b-gguf to start chatting
- Docker Model Runner
How to use Mikrodev/stcoder-gemma4-12b-gguf with Docker Model Runner:
docker model run hf.co/Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M
- Lemonade
How to use Mikrodev/stcoder-gemma4-12b-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Mikrodev/stcoder-gemma4-12b-gguf:Q4_K_M
Run and chat with the model
lemonade run user.stcoder-gemma4-12b-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| { | |
| "audio_ms_per_token": 40, | |
| "audio_seq_length": 750, | |
| "feature_extractor": { | |
| "audio_samples_per_token": 640, | |
| "feature_extractor_type": "Gemma4UnifiedAudioFeatureExtractor", | |
| "feature_size": 640, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| }, | |
| "image_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": false, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
| ], | |
| "image_processor_type": "Gemma4UnifiedImageProcessor", | |
| "image_std": [ | |
| 1.0, | |
| 1.0, | |
| 1.0 | |
| ], | |
| "max_soft_tokens": 280, | |
| "patch_size": 16, | |
| "pooling_kernel_size": 3, | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098 | |
| }, | |
| "image_seq_length": 280, | |
| "processor_class": "Gemma4UnifiedProcessor", | |
| "video_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "do_sample_frames": true, | |
| "image_mean": [ | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
| ], | |
| "image_std": [ | |
| 1.0, | |
| 1.0, | |
| 1.0 | |
| ], | |
| "max_soft_tokens": 70, | |
| "num_frames": 32, | |
| "patch_size": 16, | |
| "pooling_kernel_size": 3, | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "return_metadata": false, | |
| "video_processor_type": "Gemma4UnifiedVideoProcessor" | |
| } | |
| } | |