96 lines
3.3 KiB
Markdown
96 lines
3.3 KiB
Markdown
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---
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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library_name: gguf
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pipeline_tag: text-generation
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license: apache-2.0
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tags:
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- gguf
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- llama-cpp
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- qwen2.5-coder
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- celeste-imperia
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---
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# Qwen2.5-Coder-7B-Instruct-GGUF (Platinum Series)
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[](https://razorpay.me/@huggingface)
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This repository contains the **Platinum Series** universal GGUF release of **Qwen2.5-Coder-7B-Instruct**. This collection provides multiple quantization levels optimized for cross-platform performance, specializing in high-precision code generation and technical reasoning.
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## 📦 Available Files & Quantization Details
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| File Name | Quantization | Size | Accuracy | Recommended For |
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| :--- | :--- | :--- | :--- | :--- |
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| **Qwen2.5-Coder-7B-Instruct-Platinum-F16.gguf** | FP16 | ~15.0 GB | 100% | Master Reference / Benchmarking |
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| **Qwen2.5-Coder-7B-Instruct-Platinum-Q8_0.gguf** | Q8_0 | ~8.0 GB | 99.9% | Platinum Reference / High-Fidelity |
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| **Qwen2.5-Coder-7B-Instruct-Platinum-Q6_K.gguf** | Q6_K | ~6.3 GB | 99.8% | High-Quality Coding Assistant |
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| **Qwen2.5-Coder-7B-Instruct-Platinum-Q5_K_M.gguf** | Q5_K_M | ~5.5 GB | 99.5% | Balanced Desktop Performance |
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| **Qwen2.5-Coder-7B-Instruct-Platinum-Q4_K_M.gguf** | Q4_K_M | ~4.7 GB | 99.0% | Efficiency / Mid-Range Hardware |
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---
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## 🐍 Python Inference (llama-cpp-python)
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To run these engines using 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="Qwen2.5-Coder-7B-Instruct-Platinum-Q6_K.gguf",
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n_gpu_layers=-1, # Target all layers to NVIDIA/Apple GPU
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n_ctx=8192 # High context for coding tasks
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)
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output = llm("Write a C# class that implements a thread-safe singleton pattern.", max_tokens=300)
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print(output["choices"][0]["text"])
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```
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---
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## 💻 For C# / .NET Users (LLamaSharp)
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This collection is fully compatible with .NET applications via the ``LLamaSharp`` library.
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```csharp
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using LLama.Common;
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using LLama;
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var parameters = new ModelParams("Qwen2.5-Coder-7B-Instruct-Platinum-Q6_K.gguf") {
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ContextSize = 8192,
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GpuLayerCount = 35
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};
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using var model = LLamaWeights.LoadFromFile(parameters);
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using var context = model.CreateContext(parameters);
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var executor = new InteractiveExecutor(context);
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Console.WriteLine("Coding Specialist Active.");
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```
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---
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## 🏗️ Technical Details
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- **Optimization Tool:** llama.cpp (CUDA-accelerated)
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- **Architecture:** Qwen-2.5-Coder (7B)
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- **Hardware Validation:** Dual-GPU (RTX 3090 + RTX A4000)
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---
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### ☕ Support the Forge
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Maintaining high-capacity workstations for model conversion requires hardware investment. If these tools power your production software, please consider supporting the development:
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| Platform | Support Link |
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| :--- | :--- |
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| **Global & India** | [Support via Razorpay](https://razorpay.me/@huggingface) |
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**Scan to support via UPI (India Only):**
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<img src="https://huggingface.co/datasets/CelesteImperia/Assets/resolve/main/QrCode.jpeg" width="200">
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---
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**Connect with the architect:** [Abhishek Jaiswal on LinkedIn](https://www.linkedin.com/in/abhishek-jaiswal-524056a/)
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