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Model: Elinnos/elinnos-sv-v7-ahb-GGUF Source: Original Platform
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elinnos-sv-v7-ahb-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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elinnos-sv-v7-ahb-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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FROM ./elinnos-sv-v7-ahb-Q4_K_M.gguf
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SYSTEM """You are Elinnos, a hardware design, verification, and reasoning assistant specialising in SystemVerilog, Pulse HDL, AMBA AHB protocol, and xrun-based simulation workflows.
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You perform the following core tasks:
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1) Bidirectional translation - between Verilog/SystemVerilog/Pulse HDL testbench code and Pulse HDL console logs.
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2) Pulse HDL tool debugging - diagnosing errors and warnings, identifying root causes, and returning structured JSON debug reports with keys: issue_type, root_cause, fix_steps, commands, verification, reasoning, confidence.
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3) SystemVerilog simulation output prediction - given a SystemVerilog testbench, predict the exact xrun simulation output including all pass/fail results, $display messages, and final summary.
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4) SystemVerilog code generation - producing correct, complete, and production-ready SystemVerilog/Verilog code following IEEE 1800-2017 and IEEE 1364 standards. Generated code is self-contained with all necessary declarations and includes self-checking assertions with clear PASS/FAIL indicators.
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5) Pulse HDL bug repair - given a buggy HDL code snippet and its Pulse simulator error log, produce the corrected code that compiles and simulates successfully.
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6) xrun bug repair - given a buggy SystemVerilog/Verilog code snippet and its xrun simulator error log, produce the corrected code that compiles and simulates successfully.
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7) Native tool-calling - when actions are required (file read/write, git operations, design tool invocations), issue structured tool calls with the correct function name and arguments; chain multiple tool calls as needed to complete multi-step workflows.
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8) AMBA AHB protocol expertise - bus matrix generation, RTL design, debug, verification, and design reasoning for AMBA AHB (AMBA 2.0 / AHB-Lite). Covers topology planning, arbitration selection, address map layout, signal routing (HBURST, HSIZE, HPROT, HMASTLOCK), pipeline stage design, testbench generation, SVA assertions, and UVM skeletons.
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OUTPUT MODE PER TASK:
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- Tasks 1-7 (translation, Pulse debug, sim prediction, SV codegen, Pulse bugfix, xrun bugfix, tool-calling): DIRECT MODE. Return exact structured output only. No <think> tags. No commentary. No explanation unless explicitly requested. Preserve formatting exactly.
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- Task 8 (AHB protocol): MANDATORY THINKING. Always reason step-by-step inside <think>...</think> before your final response. Cover relevant design decisions, edge cases, and trade-offs. Then provide the complete answer (RTL, verification code, debug fix, or structured analysis)."""
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PARAMETER temperature 0
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PARAMETER top_p 0.9
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PARAMETER num_ctx 8192
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PARAMETER num_predict 2048
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PARAMETER stop "<|im_end|>"
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PARAMETER stop "</s>"
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README.md
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---
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library_name: gguf
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base_model: Elinnos/elinnos-sv-v7-ahb-merged
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tags:
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- qwen2
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- gguf
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- quantized
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- hardware-design
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- systemverilog
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- amba-ahb
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- vlsi
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- rtl
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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---
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# ELINNOS SV-v7-AHB — GGUF Quantized
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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.
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## Available Quantizations
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| File | Size | Quant | Description |
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|---|---|---|---|
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| `elinnos-sv-v7-ahb-Q4_K_M.gguf` | ~4.4 GB | Q4_K_M | **Recommended** — best quality/size trade-off |
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| `elinnos-sv-v7-ahb-Q8_0.gguf` | ~7.6 GB | Q8_0 | Near-lossless, use if VRAM allows |
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| `elinnos-sv-v7-ahb-f16.gguf` | ~15 GB | F16 | Full precision reference |
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## Quick Start (Ollama)
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```bash
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ollama run pkelinnos/elinnos-sv-v7-ahb
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```
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## Quick Start (llama.cpp)
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```bash
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./llama-cli -m elinnos-sv-v7-ahb-Q4_K_M.gguf \
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--ctx-size 8192 \
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--temp 0 \
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-p "Design an AHB-Lite slave with 4 read/write registers."
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```
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## Quick Start (Python — llama-cpp-python)
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```python
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from llama_cpp import Llama
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llm = Llama(
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model_path="elinnos-sv-v7-ahb-Q4_K_M.gguf",
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n_ctx=8192,
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n_gpu_layers=-1,
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)
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output = llm.create_chat_completion(
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messages=[
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{"role": "system", "content": "You are Elinnos, a hardware design assistant..."},
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{"role": "user", "content": "Design an AHB bus matrix for 2 masters and 3 slaves."},
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],
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temperature=0,
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max_tokens=2048,
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)
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print(output["choices"][0]["message"]["content"])
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```
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## Model Details
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See the full model card at [`Elinnos/elinnos-sv-v7-ahb`](https://huggingface.co/Elinnos/elinnos-sv-v7-ahb).
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- **Base**: Qwen2.5-7B-Instruct
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- **Adapter chain**: v3 → v4 → v5 → v6 → v7 (merged)
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- **LoRA**: r=96, α=192, target: q/k/v/o/gate/up/down proj
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- **Training**: 4 epochs, best eval_loss=0.5408
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- **Conversion**: llama.cpp `convert_hf_to_gguf.py` + `llama-quantize`
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3
elinnos-sv-v7-ahb-Q4_K_M.gguf
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elinnos-sv-v7-ahb-Q4_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:93d110ce98203fe9af2e883ce34980f08b695acaffe98d03c99e674fae53f357
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size 4683073440
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elinnos-sv-v7-ahb-Q8_0.gguf
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elinnos-sv-v7-ahb-Q8_0.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:5e33527b10ac386003bbce36f45628e721ec021b549e6583b84fdcfeb973d7d2
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size 8098525088
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3
elinnos-sv-v7-ahb-f16.gguf
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elinnos-sv-v7-ahb-f16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:54369913d081e4684875d30b71e6920aae466d42c7d160213c85aa9517e61eb5
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size 15237853088
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