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Model: g023/qwen3-tiny-v2 Source: Original Platform
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+---
+license: apache-2.0
+language:
+  - en
+base_model: Qwen/Qwen3-1.7B
+tags:
+  - qwen3
+  - gguf
+  - layer-surgery
+  - small-language-model
+  - optimized
+  - thinking
+  - text-generation
+  - skip-connections
+  - interpolation
+model_name: Qwen3-g023-tiny-v2
+pipeline_tag: text-generation
+library_name: llama.cpp
+quantized_by: g023
+---
+
+# Qwen3-g023-tiny-v2 — GGUF
+
+**An advanced 30-layer Qwen3 variant using swap, interpolation, and skip-bridge surgery.**
+
+Created through innovative layer surgery combining multi-swap, interpolation, and bridge (skip connection) techniques. Scores **94.3/100** — a 6.5-point improvement over the original Qwen3-1.7B baseline (87.8/100) and the highest score achieved in two phases of experimentation across ~250 configurations. (I have my own benchmarks, so results may vary if you run your own tests.)
+
+## Available Quantizations
+
+| Quantization | Bits/Weight | Description | Download |
+|:---:|:---:|:---|:---:|
+| **Q8_0** | 8.00 | Highest quality, virtually lossless (USE THIS ONE) | [Qwen3-g023-tiny-v2-Q8_0.gguf](./Qwen3-g023-tiny-v2-Q8_0.gguf) |
+| **Q6_K** | 6.57 | Excellent quality, good compression | [Qwen3-g023-tiny-v2-Q6_K.gguf](./Qwen3-g023-tiny-v2-Q6_K.gguf) |
+| **Q4_K_M** | 4.85 | Good balance of quality and size | [Qwen3-g023-tiny-v2-Q4_K_M.gguf](./Qwen3-g023-tiny-v2-Q4_K_M.gguf) |
+| **Q3_K_M** | 3.91 | High compression, moderate quality loss | [Qwen3-g023-tiny-v2-Q3_K_M.gguf](./Qwen3-g023-tiny-v2-Q3_K_M.gguf) |
+| **Q2_K** | 3.35 | Maximum compression, significant quality loss | [Qwen3-g023-tiny-v2-Q2_K.gguf](./Qwen3-g023-tiny-v2-Q2_K.gguf) |
+
+## Model Details
+
+| Parameter | Value |
+|:---|:---|
+| Architecture | Qwen3ForCausalLM |
+| Layers | **30** (28 original + 2 from surgery) |
+| Hidden Size | 2,048 |
+| Intermediate Size | 6,144 |
+| Attention Heads | 16 query / 8 key-value (GQA) |
+| Head Dimension | 128 |
+| Vocabulary | 151,936 tokens |
+| Max Context | 40,960 tokens |
+| RoPE θ | 1,000,000 |
+| Tied Embeddings | Yes |
+| Total Parameters | **~1.82B** |
+| Precision (source) | bfloat16 |
+
+## Surgery Operations
+
+This model was created by applying three innovative surgical operations to [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B):
+
+1. **Multi-swap: layers 12↔13 and 16↔17** — Reorders attention blocks at two critical points in the network for improved representational flow through the mid-layers.
+2. **Interpolation: layers 20 & 22 (α=0.5)** — Creates a new layer by blending the weights of layers 20 and 22 at equal proportions, producing a smoother transition in the upper layers.
+3. **Bridge (skip connection): layer 5 → after layer 20** — Copies early-layer representations (layer 5) and inserts them after layer 20, creating a skip connection that helps preserve low-level features deep in the network.
+
+### Why These Operations Work
+
+- **Multi-swap** corrects suboptimal layer ordering that emerged from pre-training, allowing better gradient flow through the network's critical middle section.
+- **Interpolation** creates a synthetic transition layer that smooths the representation gap between layers 20 and 22, reducing the information bottleneck.
+- **Bridge/skip connections** address the "forgetting problem" in deep networks by reintroducing early feature representations at later stages — a technique inspired by ResNet's residual connections but applied at the transformer layer level.
+
+## Benchmark Results
+
+| Metric | Original (28L) | [v1 (27L)](https://huggingface.co/g023/Qwen3-g023-tiny-v1-GGUF) | **v2 (30L)** | Δ vs Original |
+|:---|:---:|:---:|:---:|:---:|
+| **Overall Score** | 87.8 / 100 | 92.9 / 100 | **94.3 / 100** | **+6.5** |
+| **Factual Accuracy** | 15/17 (88%) | 17/17 (100%) | **16/17 (94%)** | **+6%** |
+| Avg Perplexity | — | 15.70 | **15.17** | — |
+| Thinking Mode | ✅ | ✅ | ✅ | — |
+| Non-Thinking Mode | ✅ | ✅ | ✅ | — |
+
+Evaluated using a comprehensive test suite with 17 factual questions, 2 completion coherence tests, perplexity measurements, repetition analysis, and thinking/non-thinking mode verification.
+
+## Features
+
+- **Thinking mode**: Full `<think>` / `</think>` reasoning support — toggle via `enable_thinking` parameter
+- **Non-thinking mode**: Direct responses without chain-of-thought overhead
+- **Tool calling**: Full function/tool calling support
+- **System prompts**: Standard system message support
+- **Chat template**: Qwen3 ChatML template embedded in the GGUF
+
+## Usage
+
+### With Ollama
+
+```bash
+# Download the GGUF and create from Modelfile
+cat > Modelfile << 'EOF'
+FROM ./Qwen3-g023-tiny-v2-Q8_0.gguf
+
+PARAMETER temperature 1.0
+PARAMETER top_p 0.95
+PARAMETER top_k 45
+PARAMETER min_p 0.1
+PARAMETER num_ctx 40000
+PARAMETER mirostat 2
+PARAMETER mirostat_tau 5.0
+PARAMETER mirostat_eta 0.1
+PARAMETER repeat_last_n 16384
+PARAMETER repeat_penalty 1.1
+PARAMETER presence_penalty 0.5
+PARAMETER frequency_penalty 1.0
+
+TEMPLATE """{{- if .System }}
+<|im_start|>system
+{{ .System }}<|im_end|>
+{{ end }}
+{{- range .Messages }}
+{{- if eq .Role "user" }}
+<|im_start|>user
+{{ .Content }}<|im_end|>
+{{- else if eq .Role "assistant" }}
+<|im_start|>assistant
+{{ .Content }}<|im_end|>
+{{- end }}
+{{- end }}
+<|im_start|>assistant
+"""
+SYSTEM "You are a helpful assistant."
+EOF
+
+ollama create qwen3-tiny-v2 -f Modelfile
+ollama run qwen3-tiny-v2
+```
+
+### With llama.cpp
+
+```bash
+# Interactive chat
+llama-cli -m Qwen3-g023-tiny-v2-Q8_0.gguf \
+  --chat-template chatml -cnv
+
+# Thinking mode
+llama-cli -m Qwen3-g023-tiny-v2-Q8_0.gguf \
+  -p "<|im_start|>user\nExplain quantum computing<|im_end|>\n<|im_start|>assistant\n<think>\n" \
+  -n 512
+
+# Non-thinking mode
+llama-cli -m Qwen3-g023-tiny-v2-Q8_0.gguf \
+  -p "<|im_start|>user\n/no_think What is 2+2?<|im_end|>\n<|im_start|>assistant\n" \
+  -n 128
+```
+
+### With Python (llama-cpp-python)
+
+```python
+from llama_cpp import Llama
+
+model = Llama("Qwen3-g023-tiny-v2-Q8_0.gguf", n_ctx=4096)
+response = model.create_chat_completion(
+    messages=[
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "What is the capital of France?"},
+    ],
+    temperature=0.6,
+)
+print(response["choices"][0]["message"]["content"])
+```
+
+## System Requirements
+
+| Quantization | RAM (CPU) | VRAM (GPU) |
+|:---:|:---:|:---:|
+| Q8_0 | ~2.2 GB | ~2.2 GB |
+| Q6_K | ~1.8 GB | ~1.8 GB |
+| Q4_K_M | ~1.4 GB | ~1.4 GB |
+| Q3_K_M | ~1.2 GB | ~1.2 GB |
+| Q2_K | ~1.0 GB | ~1.0 GB |
+
+## v1 vs v2
+
+This model (v2) is the **Phase 2 champion**, using advanced multi-operation surgery for the highest overall score.
+
+| | [v1](https://huggingface.co/g023/Qwen3-g023-tiny-v1-GGUF) | v2 (this model) |
+|:---|:---:|:---:|
+| Layers | 27 | 30 |
+| Parameters | ~1.67B | ~1.82B |
+| Operations | del + swap | swap + interpolate + bridge |
+| Score | 92.9 / 100 | 94.3 / 100 |
+| Factual | 100% (17/17) | 94% (16/17) |
+| Perplexity | 15.70 | 15.17 |
+| Use Case | Max factual accuracy | Max overall score |
+
+**v1** is recommended when factual accuracy is paramount (100% vs 94%).
+**v2** is recommended when overall quality matters more (94.3 vs 92.9).
+
+## Methodology
+
+Layer surgery was performed through a systematic, test-driven process across two phases:
+
+1. **Phase 1** (~150 configs): Exhaustive search across deletion, duplication, swapping, interpolation, and combined operations → champion: del_10 + swap_11↔12 (v1)
+2. **Phase 2** (~95 configs): Advanced techniques including tripling, multi-swap, layer reversal, cycling, weight scaling, layer merging, skip bridges, and synthesis → champion: this model (v2)
+3. **Evaluation**: Each configuration scored on factual accuracy (17 questions), completion coherence, perplexity, repetition ratio, and thinking mode functionality
+
+### Phase 2 Leaderboard (Top 5)
+
+| Rank | Configuration | Score | Factual | PPL |
+|:---:|:---|:---:|:---:|:---:|
+| 🥇 | swap(12↔13,16↔17) + interp(20↔22) + bridge(5→20) | **94.3** | 94% | 15.17 |
+| 🥈 | swap(12↔13,16↔17) + interp(20↔22) | 93.9 | 94% | 14.74 |
+| 🥉 | swap(12↔13) + interp(20↔22) + bridge(5→20) | 93.4 | 94% | 15.66 |
+| 4 | multi-swap(12↔13,16↔17) | 93.1 | 100% | 14.90 |
+| 5 | Phase 1 champion (del_10 + swap_11↔12) | 92.9 | 100% | 15.70 |
+
+## Credits
+
+- **Base model**: [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) by the Qwen team at Alibaba
+- **Quantization**: llama.cpp
+- **Surgery**: g023
+
+## License
+
+Apache 2.0 — same as the original Qwen3-1.7B model.