Text Generation
MLX
Safetensors
gemma4_unified
nvfp4
krill
gemma4
apple-silicon
agentic
tool-use
conversational
Instructions to use srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4 with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4"
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 srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4
Run Hermes
hermes
- MLX LM
How to use srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "srv-sngh/gemma-4-12B-agentic-fable5-composer2.5-v2-nvfp4", "messages": [ {"role": "user", "content": "Hello"} ] }'
Card: add agentic HumanEval+ and base MBPP+ partial cells
Browse files
README.md
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@@ -62,10 +62,10 @@ EvalPlus set; GSM8K is a 150‑problem subset, 8‑shot. **Not** EvalPlus‑lead
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| Model | mode | HumanEval | HumanEval+ | MBPP | MBPP+ | GSM8K |
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| Google gemma-4-12B-it (base) | off | 57.3 | 56.7 | 42.1 |
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| Google gemma-4-12B-it (base) | on | 48.8 | 48.8 | 49.5 |
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| agentic v2 (this model) | off | 83.5 |
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| agentic v2 (this model) | on | 86.0 |
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> ⚠️ **Partial results — this run is still in progress.** Empty cells (—) are filling in; the card will be updated as the full sweep (coder + remaining agentic/GSM8K) completes.
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| Model | mode | HumanEval | HumanEval+ | MBPP | MBPP+ | GSM8K |
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| Google gemma-4-12B-it (base) | off | 57.3 | 56.7 | 42.1 | 37.6 | 95.3 |
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| Google gemma-4-12B-it (base) | on | 48.8 | 48.8 | 49.5 | 43.9 | — |
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| agentic v2 (this model) | off | 83.5 | 81.7 | — | — | — |
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| agentic v2 (this model) | on | 86.0 | 82.9 | — | — | — |
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> ⚠️ **Partial results — this run is still in progress.** Empty cells (—) are filling in; the card will be updated as the full sweep (coder + remaining agentic/GSM8K) completes.
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