Instructions to use sjakek/gemma4-12b-mtp-assistant 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 sjakek/gemma4-12b-mtp-assistant 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 sjakek/gemma4-12b-mtp-assistant:BF16 # Run inference directly in the terminal: llama cli -hf sjakek/gemma4-12b-mtp-assistant:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf sjakek/gemma4-12b-mtp-assistant:BF16 # Run inference directly in the terminal: llama cli -hf sjakek/gemma4-12b-mtp-assistant:BF16
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 sjakek/gemma4-12b-mtp-assistant:BF16 # Run inference directly in the terminal: ./llama-cli -hf sjakek/gemma4-12b-mtp-assistant:BF16
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 sjakek/gemma4-12b-mtp-assistant:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf sjakek/gemma4-12b-mtp-assistant:BF16
Use Docker
docker model run hf.co/sjakek/gemma4-12b-mtp-assistant:BF16
- LM Studio
- Jan
- vLLM
How to use sjakek/gemma4-12b-mtp-assistant with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sjakek/gemma4-12b-mtp-assistant" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sjakek/gemma4-12b-mtp-assistant", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sjakek/gemma4-12b-mtp-assistant:BF16
- Ollama
How to use sjakek/gemma4-12b-mtp-assistant with Ollama:
ollama run hf.co/sjakek/gemma4-12b-mtp-assistant:BF16
- Unsloth Studio
How to use sjakek/gemma4-12b-mtp-assistant 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 sjakek/gemma4-12b-mtp-assistant 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 sjakek/gemma4-12b-mtp-assistant to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sjakek/gemma4-12b-mtp-assistant to start chatting
- Docker Model Runner
How to use sjakek/gemma4-12b-mtp-assistant with Docker Model Runner:
docker model run hf.co/sjakek/gemma4-12b-mtp-assistant:BF16
- Lemonade
How to use sjakek/gemma4-12b-mtp-assistant with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sjakek/gemma4-12b-mtp-assistant:BF16
Run and chat with the model
lemonade run user.gemma4-12b-mtp-assistant-BF16
List all available models
lemonade list
- Atomic Chat
File size: 2,835 Bytes
62b827c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | {
"source_model": "google/gemma-4-12B-it-assistant",
"source_revision": "723932f88886ab714522468b94f9c7ee48d8c9a8",
"requested_repo": "atx/gemma4-12b-mtp-assistant",
"uploaded_repo": "sjakek/gemma4-12b-mtp-assistant",
"requested_repo_status": "blocked: authenticated token has no atx namespace write rights",
"gguf_architecture": "gemma4-assistant",
"llama_cpp_branch": {
"repo": "https://github.com/am17an/llama.cpp",
"branch": "gemma4-mtp",
"commit": "b8e703e",
"local_converter_patch": [
"Register Gemma4UnifiedAssistantForCausalLM in conversion/__init__.py",
"Register Gemma4UnifiedAssistantForCausalLM on Gemma4AssistantModel in conversion/gemma.py"
]
},
"outputs": [
{
"filename": "gemma-4-12B-it-assistant-BF16.gguf",
"file_type": "MOSTLY_BF16",
"bytes": 861520128,
"sha256": "be2ff6cf6dc9f4d753be846efb990606a5fec1b9c758c7f200112d2431f5e248"
},
{
"filename": "gemma-4-12B-it-assistant-Q8_0.gguf",
"file_type": "MOSTLY_Q8_0",
"bytes": 465109248,
"sha256": "cb9b46d9ff820b2b9b0d53cc911a2bc27eb2faf84700284047244d8f28883794"
}
],
"metadata": {
"context_length": 131072,
"assistant_hidden_size": 1024,
"target_hidden_size": 3840,
"num_hidden_layers": 4,
"num_attention_heads": 16,
"head_count_kv": [8, 8, 8, 1],
"shared_kv_layers": 4,
"nextn_predict_layers": 4,
"sliding_window_pattern": [true, true, true, false],
"rope_dimension_count": 512,
"rope_dimension_count_swa": 256,
"required_tensors": [
"rope_freqs.weight",
"nextn.pre_projection.weight",
"nextn.post_projection.weight"
]
},
"runtime_validation": {
"status": "pass",
"target_model": "gemma-4-12b-it-UD-Q6_K_XL.gguf",
"speculative_type": "draft-mtp",
"serving_shape": {
"ctx_size": 131072,
"batch_size": 4096,
"ubatch_size": 512,
"flash_attn": true,
"draft_kv": "q8_0/q8_0"
},
"checks": [
{
"name": "gguf_audit",
"result": "pass"
},
{
"name": "bf16_mtp_generation",
"result": "pass",
"draft_tokens": 6,
"accepted_tokens": 6,
"log": "logs/completion-bf16-mtp.json"
},
{
"name": "q8_0_mtp_generation",
"result": "pass",
"draft_tokens": 6,
"accepted_tokens": 6,
"log": "logs/completion-q8-mtp.json"
},
{
"name": "long_context_smoke",
"result": "pass",
"prompt_tokens": 126009,
"predicted_tokens": 8,
"truncated": false,
"log": "logs/completion-q8-mtp-long-context-summary.json"
},
{
"name": "openai_chat_completion",
"result": "pass",
"log": "logs/openai-chat-final-q8-canonical.json"
}
]
}
}
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