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VeriReason Qwen2.5 7B RTLCoder Verilog GRPO Reasoning Tb by Nellyw888

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VeriReason Qwen2.5 7B RTLCoder Verilog GRPO Reasoning Tb is an open-source language model by Nellyw888. Features: 7b LLM, VRAM: 14.6GB, Context: 32K, Instruction-Based, Code Generating, LLM Explorer Score: 0.21.

  Arxiv:2505.11849   Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-...   Codegen Dataset:nellyw888/verireason-r...   Endpoints compatible   Instruct   Qwen2   Reasoning   Region:us   Rtl   Safetensors   Sharded   Tensorflow   Verilog
Model Card on HF 🤗: https://huggingface.co/Nellyw888/VeriReason-Qwen2.5-7b-RTLCoder-Verilog-GRPO-reasoning-tb 

VeriReason Qwen2.5 7B RTLCoder Verilog GRPO Reasoning Tb Benchmarks

LLME Score: 0.20878
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
VeriReason Qwen2.5 7B RTLCoder Verilog GRPO Reasoning Tb (Nellyw888/VeriReason-Qwen2.5-7b-RTLCoder-Verilog-GRPO-reasoning-tb)
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VeriReason Qwen2.5 7B RTLCoder Verilog GRPO Reasoning Tb Parameters and Internals

LLM NameVeriReason Qwen2.5 7B RTLCoder Verilog GRPO Reasoning Tb
Repository 🤗https://huggingface.co/Nellyw888/VeriReason-Qwen2.5-7b-RTLCoder-Verilog-GRPO-reasoning-tb 
Base Model(s)  Qwen/Qwen2.5-Coder-7B-Instruct   Qwen/Qwen2.5-Coder-7B-Instruct
Model Size7b
Required VRAM14.6 GB
Updated2025-09-23
MaintainerNellyw888
Model Typeqwen2
Instruction-BasedYes
Model Files  2.2 GB: 1-of-105   0.3 GB: 2-of-105   0.3 GB: 3-of-105   0.3 GB: 4-of-105   0.2 GB: 5-of-105   0.3 GB: 6-of-105   0.3 GB: 7-of-105   0.3 GB: 8-of-105   0.3 GB: 9-of-105   0.3 GB: 10-of-105   0.3 GB: 11-of-105   0.2 GB: 12-of-105   0.3 GB: 13-of-105   0.3 GB: 14-of-105   0.3 GB: 15-of-105   0.2 GB: 16-of-105   0.3 GB: 17-of-105   0.3 GB: 18-of-105   0.3 GB: 19-of-105   0.3 GB: 20-of-105   0.3 GB: 21-of-105   0.3 GB: 22-of-105   0.2 GB: 23-of-105   0.3 GB: 24-of-105   0.3 GB: 25-of-105   0.3 GB: 26-of-105   0.2 GB: 27-of-105   0.3 GB: 28-of-105   0.3 GB: 29-of-105   0.3 GB: 30-of-105   0.3 GB: 31-of-105   0.3 GB: 32-of-105   0.3 GB: 33-of-105   0.2 GB: 34-of-105   0.3 GB: 35-of-105   0.3 GB: 36-of-105   0.3 GB: 37-of-105   0.2 GB: 38-of-105   0.3 GB: 39-of-105   0.3 GB: 40-of-105   0.3 GB: 41-of-105   0.3 GB: 42-of-105   0.3 GB: 43-of-105   0.3 GB: 44-of-105   0.2 GB: 45-of-105
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.51.3
Vocabulary Size152064
Torch Data Typefloat32

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Qwen2.5 7B Rebase986K / 15.2 GB732
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Tessa T1 7B117K / 15.2 GB1210
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Qwen2.5 Coder 7B Instruct32K / 15.2 GB2110918684
AstraGPTCoder 7B32K / 15.2 GB3421
Qwen2.5 7B MS Destroyer32K / 15.2 GB71
Qwen2.5 Coder 7B Instruct MLX32K / 15.2 GB6222
Note: green Score (e.g. "73.2") means that the model is better than Nellyw888/VeriReason-Qwen2.5-7b-RTLCoder-Verilog-GRPO-reasoning-tb.

Rank the VeriReason Qwen2.5 7B RTLCoder Verilog GRPO Reasoning Tb Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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