---
library_name: gguf
base_model: Elinnos/elinnos-sv-v7-ahb-merged
tags:
  - qwen2
  - gguf
  - quantized
  - hardware-design
  - systemverilog
  - amba-ahb
  - vlsi
  - rtl
license: apache-2.0
language:
  - en
pipeline_tag: text-generation
---

# ELINNOS SV-v7-AHB — GGUF Quantized

GGUF quantized versions of [`Elinnos/elinnos-sv-v7-ahb-merged`](https://huggingface.co/Elinnos/elinnos-sv-v7-ahb-merged), the merged ELINNOS SV-v7-AHB model fine-tuned on AMBA AHB hardware design tasks.

## Available Quantizations

| File | Size | Quant | Description |
|---|---|---|---|
| `elinnos-sv-v7-ahb-Q4_K_M.gguf` | ~4.4 GB | Q4_K_M | **Recommended** — best quality/size trade-off |
| `elinnos-sv-v7-ahb-Q8_0.gguf` | ~7.6 GB | Q8_0 | Near-lossless, use if VRAM allows |
| `elinnos-sv-v7-ahb-f16.gguf` | ~15 GB | F16 | Full precision reference |

## Quick Start (Ollama)

```bash
ollama run pkelinnos/elinnos-sv-v7-ahb
```

## Quick Start (llama.cpp)

```bash
./llama-cli -m elinnos-sv-v7-ahb-Q4_K_M.gguf \
  --ctx-size 8192 \
  --temp 0 \
  -p "Design an AHB-Lite slave with 4 read/write registers."
```

## Quick Start (Python — llama-cpp-python)

```python
from llama_cpp import Llama

llm = Llama(
    model_path="elinnos-sv-v7-ahb-Q4_K_M.gguf",
    n_ctx=8192,
    n_gpu_layers=-1,
)
output = llm.create_chat_completion(
    messages=[
        {"role": "system", "content": "You are Elinnos, a hardware design assistant..."},
        {"role": "user",   "content": "Design an AHB bus matrix for 2 masters and 3 slaves."},
    ],
    temperature=0,
    max_tokens=2048,
)
print(output["choices"][0]["message"]["content"])
```

## Model Details

See the full model card at [`Elinnos/elinnos-sv-v7-ahb`](https://huggingface.co/Elinnos/elinnos-sv-v7-ahb).

- **Base**: Qwen2.5-7B-Instruct
- **Adapter chain**: v3 → v4 → v5 → v6 → v7 (merged)
- **LoRA**: r=96, α=192, target: q/k/v/o/gate/up/down proj
- **Training**: 4 epochs, best eval_loss=0.5408
- **Conversion**: llama.cpp `convert_hf_to_gguf.py` + `llama-quantize`