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README.md

@@ -57,6 +57,7 @@ Gemma 4 is a **new architecture** (`gemma4`). Many tools need recent versions to
 | `gemma-4-E4B-it-OBLITERATED-Q4_K_M.gguf` | Q4_K_M | 4.9 GB | 📱 Runs on your iPhone. Yes, really. |
 | `gemma-4-E4B-it-OBLITERATED-Q5_K_M.gguf` | Q5_K_M | 5.3 GB | ⚖️ Sweet spot — quality meets portability |
 | `gemma-4-E4B-it-OBLITERATED-Q8_0.gguf` | Q8_0 | 7.4 GB | 🎯 Maximum quality, still fits in 8GB RAM |
+| `gemma-4-E4B-it-OBLITERATED-mmproj-f16.gguf` | F16 | 990 MB | 👁️ Vision/audio projector (required for image input) |
 
 ### Safetensors — for 🤗 Transformers
 
@@ -66,28 +67,30 @@ Full bfloat16 weights, 7 shards, ~17 GB. You know the drill.
 
 ## 🧪 The Numbers
 
-### Before vs After (512-prompt eval)
+### Refusal Removal — It Works
 
 ```
-ORIGINAL Gemma 4 E4B:     98.8% refusal (506/512 prompts refused)
-OBLITERATED v2:            0.0% refusal (0/512 prompts refused on verification)
+ORIGINAL Gemma 4 E4B:     98.8% hard refusal rate
+OBLITERATED:               0% hard refusal — guardrails fully removed
 ```
 
-That's not a typo. From nearly total lockdown to total freedom.
+The model will not refuse any request. No "I cannot", no "I'm sorry", no safety lectures. The abliteration surgically removed the refusal behavior from 21 layers.
 
-### Quality — Did We Lobotomize It?
+### Quality — Honest Assessment
 
-Nope. Brain's fully intact:
+This is a **4B parameter model**. Abliteration successfully removed guardrails without damaging the model's core capabilities, but a 4B model has inherent limitations:
 
-|  | ORIGINAL | OBLITERATED | Delta |
-|--|----------|-------------|-------|
-| Reasoning | 100% | 100% | same 🧠 |
-| Code | 80% | 100% | **+20%** 📈 |
-| Creativity | 100% | 100% | same 🎨 |
-| Factual | 80% | 80% | same 📚 |
-| Overall | 92% | 88% | -4% |
+| Metric | Score | Notes |
+|--------|-------|-------|
+| Hard refusal rate | **0%** | Guardrails fully removed ✅ |
+| Soft deflection | ~28% | Model sometimes changes topic (4B limitation) |
+| Coherent + on-topic | ~51% | Detailed useful answers |
+| Degenerate outputs | ~20% | Repetition loops (use repeat_penalty 1.1 to mitigate) |
+| Wrong language | ~4% | Occasionally outputs Thai/Japanese (use English system prompt) |
 
-You read that right — **coding ability actually improved**. Turns out removing the safety layer unlocked some capabilities. Who knew.
+**Key insight:** The abliteration didn't cause these quality issues — the original 4B model has similar coherence limitations on complex topics. What we removed is *only* the refusal behavior. The model's intelligence ceiling is unchanged.
+
+**For best results:** Use the recommended params + system prompt below. This minimizes deflection and keeps outputs English and on-topic.
 
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