Wild Gemma 4 E4B

Savanna Sentinel fine-tune of Gemma 4 E4B IT for camera-trap wildlife monitoring.

This model reads image+text camera-trap prompts and is optimized to return structured JSON for Serengeti-style event interpretation, review routing, and biodiversity reporting workflows.

Run

ollama run alfaxad/wild-gemma4:e4b

Recommended Sampling

The model was evaluated with the Gemma 4/Ollama recommended sampling defaults:

temperature 1.0
top_p 0.95
top_k 64

Prompting

Use image content before text content. Ask for strict JSON and validate the response before using it in a product workflow.

Example system prompt:

You are Savanna Sentinel. Return only valid JSON.

Example user prompt:

Classify this Serengeti camera-trap capture event. Use the image burst first, then the metadata. Return JSON with keys blank, detections, and review.

Thinking Mode

Gemma 4 supports thinking mode in Ollama. For JSON production, prefer non-thinking mode when you need short schema-only responses. Use thinking mode for harder visual reasoning checks, then strip any thought content and validate only the final JSON.

Do not carry thought content forward in multi-turn history.

Expected Output Shape

{
  "schema_version": "savanna_sentinel_event_v1",
  "capture_event_id": "ASG...",
  "blank": false,
  "detections": [
    {
      "species": "zebra",
      "count_bin": "3",
      "behaviors": {
        "standing": false,
        "resting": false,
        "moving": true,
        "eating": false,
        "interacting": false
      },
      "young_present": false,
      "confidence": "high",
      "evidence": {
        "visual_basis": "Striped equids visible across the image burst.",
        "frames_used": [1, 2, 3]
      }
    }
  ],
  "review": {
    "review_needed": false,
    "reasons": []
  }
}

Evaluation Snapshot

Diagnostic eval on the corrected Ollama/GGUF export:

These are small diagnostic checks, not a final scientific benchmark.

Artifacts

• Merged HF model: https://huggingface.co/Alfaxad/wild-gemma-4-E4B-it
• GGUF export and metrics: https://huggingface.co/Alfaxad/wild-gemma-4-E4B-it-GGUF
• Training/eval dataset: https://huggingface.co/datasets/Alfaxad/wildlife-sentinel
• Base Gemma 4 E4B IT: https://huggingface.co/google/gemma-4-E4B-it

Limitations

• JSON validity is not guaranteed; always parse and schema-validate.
• The model is specialized for Snapshot Serengeti-style camera-trap data and may not generalize to other camera systems or regions without validation.
• The Ollama artifact is Q4_K_M quantized, so behavior can differ from the merged HF model.
• Audio support from the base model family was not evaluated for this Savanna Sentinel release.