Instructions to use Pablo-Flores-Mollinedo/verilog-rtl-lora-adapter-suite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Pablo-Flores-Mollinedo/verilog-rtl-lora-adapter-suite with PEFT:
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- Notebooks
- Google Colab
- Kaggle
Verilog RTL LoRA Adapter Suite (TCAD 2026 Draft Artifacts)
This repository collects the main PEFT LoRA adapters used in the adapter-centric Verilog RTL generation study. The original local adapter directories were copied and renamed with descriptive artifact names. No original local adapter directory was deleted or modified.
Adapter mapping
| Descriptive artifact name | Paper alias | Base/start | Intended role |
|---|---|---|---|
qwen25-coder-7b-verilog-direct-baseline-lora |
v9 |
Qwen2.5-Coder-7B-Instruct | Stable direct LoRA baseline trained from auto-distilled RTL data and passing anchors. |
qwen25-coder-7b-verilog-delta-distilled-lora |
v30b |
Qwen2.5-Coder-7B-Instruct + v9 |
Delta-distilled direct adapter emphasizing cases where v9 failed and a verifier/selector found a passing candidate. |
qwen35-9b-verilog-migration-general-lora |
v32 |
Qwen3.5-9B | First Qwen3.5 migration adapter trained from Qwen2.5-derived verified data. |
qwen35-9b-verilog-thinking-reinforced-lora |
v33 |
Qwen3.5-9B + v32 |
Thinking/reasoning-preserving direct adapter with failure-analysis reinforcement and passing anchors. |
qwen35-9b-verilog-structured-repair-lora |
v34 |
Qwen3.5-9B + v33 |
Structured/manual repair adapter focused on deterministic final-code formatting and repair behavior. |
v36 in the paper is not a separate adapter. It is a verification-guided workflow that composes the v33 and v34 adapters with compiler/simulator feedback under a bounded call budget.
Loading example
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
base_model = "Qwen/Qwen2.5-Coder-7B-Instruct" # for v9/v30b artifacts
adapter_dir = "qwen25-coder-7b-verilog-direct-baseline-lora"
tok = AutoTokenizer.from_pretrained(adapter_dir)
base = AutoModelForCausalLM.from_pretrained(base_model, device_map="auto")
model = PeftModel.from_pretrained(base, adapter_dir)
Use Qwen/Qwen3.5-9B as the base family for the Qwen3.5 adapters (v32, v33, v34) with the compatibility loader used in the project scripts.
Reporting note
These adapters are research artifacts. Several training rows are benchmark-targeted or verifier-derived. Do not report them as clean zero-shot leaderboard submissions on the same benchmark. Direct adapter results and verification-guided workflow results should be reported separately.
Internal diagnostic benchmark
This repository also includes internal-rtl-diagnostic-30/, the Internal RTL Diagnostic-30 suite used for local regression testing and adapter sanity checks. It is an internal diagnostic benchmark, not a public leaderboard. Results on this suite should not be compared to external adapters/models unless prompts, harness, extraction, simulator, and scoring protocol are matched.
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