Qwen2.5-Coder-7B-Instruct-OpenVINO-INT8 (Silver Series)

This repository contains the Silver Series optimized OpenVINO™ IR version of Qwen2.5-Coder-7B-Instruct, quantized to INT8 precision using NNCF. This model is the premier choice for local C# development assistance, offering high-fidelity code generation and technical reasoning.

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🐍 Python Inference (Optimum-Intel)

To run this Silver Series coder locally using the optimum-intel library:

from optimum.intel import OVModelForCausalLM
from transformers import AutoTokenizer

model_id = "CelesteImperia/Qwen2.5-Coder-7B-Instruct-OpenVINO-INT8"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = OVModelForCausalLM.from_pretrained(model_id)

prompt = "Write a thread-safe Singleton pattern in C# using Lazy<T>."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=500)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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💻 For C# / .NET Users (OpenVINO.GenAI)

The Qwen2.5 Coder is optimized for the native OpenVINO.GenAI framework, providing a low-latency coding companion directly within your Windows development environment.

using OpenVino.GenAI;

// 1. Initialize the LLM Pipeline
var device = "CPU"; // Use "GPU" to leverage RTX 3090/A4000
using var pipe = new LLMPipeline("path/to/qwen2.5-coder-int8-model", device);

// 2. Set Generation Config
var config = new GenerationConfig { MaxNewTokens = 1024, Temperature = 0.2f }; // Low temp for precise code

// 3. Execute Inference
var prompt = "Generate a C# WPF ViewModel for a real-time hardware monitoring dashboard.";
var result = pipe.Generate(prompt, config);

Console.WriteLine(result);

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🏗️ Technical Details

• Optimization Tool: NNCF (Neural Network Compression Framework)
• Quantization: INT8 Symmetric (Per-channel)
• Primary Domain: Software Engineering / Coding
• Workstation Validation: Dual-GPU (RTX 3090 + RTX A4000)

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📜 License

This model is released under the Apache 2.0 License.

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Connect with the architect: Abhishek Jaiswal on LinkedIn