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license: apache-2.0 |
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<div align="center"> |
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<img src="./assets/logo.png" style="zoom:25%;" /> |
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</div> |
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# CodeV:Empowering LLMs for Verilog Generation through Multi-Level Summarization |
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<img src="assets/overview.png" style="zoom:50%;" /> |
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CodeV is an innovative series of open-source, instruction-tuned Large Language Models (LLMs) specifically designed for the generation of high-quality Verilog code, addressing the challenges faced by existing models in this domain. **(This repo is under development)** |
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## Models and Datasets |
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| | Base Model | CodeV | |
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| ---- | --------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------ | |
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| 6.7B | [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) | [[zyyy1023399127/CodeV-DS-6.7B](https://huggingface.co/zyyy1023399127/CodeV-DS-6.7B) | |
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| 7B | [codellama/CodeLlama-7b-Python-hf](https://huggingface.co/codellama/CodeLlama-7b-Python-hf) | [zyyy1023399127/CodeV-CL-7B](https://huggingface.co/zyyy1023399127/CodeV-CL-7B) | |
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| 7B | [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat) | [zyyy1023399127/CodeV-QW-7B](https://huggingface.co/zyyy1023399127/CodeV-QW-7B) | |
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## Test |
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If you want to test the generation capability of existing models on Verilog, you need to install the [VerilogEval](https://github.com/NVlabs/verilog-eval) and [RTLLM](https://github.com/hkust-zhiyao/rtllm) environments. |
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## Quick Start |
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```python |
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from transformers import pipeline |
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import torch |
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prompt= "FILL IN THE QUESTION" |
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generator = pipeline( |
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model="CODEV", |
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task="text-generation", |
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torch_dtype=torch.bfloat16, |
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device_map="auto", |
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) |
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result = generator(prompt , max_length=2048, num_return_sequences=1, temperature=0.0) |
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response = result[0]["generated_text"] |
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print("Response:", response) |
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``` |
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## Acknowledgements |
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* [Magicoder](https://github.com/ise-uiuc/magicoder): Training code, original datasets and data decontamination |
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* [DeepSeek-Coder](https://github.com/deepseek-ai/DeepSeek-Coder): Base model for CodeV-DeepSeek |
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* [CodeLlama](https://ai.meta.com/research/publications/code-llama-open-foundation-models-for-code/): Base model for CodeLlama |
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* [CodeQwen](https://github.com/QwenLM/CodeQwen1.5): CodeV-CodeQwen |
