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Model: CelesteImperia/Phi-3.5-mini-instruct-Platinum-GGUF Source: Original Platform
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LICENSE
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LICENSE
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MIT License
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Copyright (c) 2024 Microsoft
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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Phi-3.5-mini-instruct-Platinum-F16.gguf
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Phi-3.5-mini-instruct-Platinum-Q8_0.gguf
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README.md
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---
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base_model: microsoft/Phi-3.5-mini-instruct
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library_name: gguf
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pipeline_tag: text-generation
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license: mit
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tags:
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- gguf
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- llama-cpp
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- phi-3.5
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- celeste-imperia
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---
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# Phi-3.5-mini-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 **Phi-3.5-mini-instruct**. This collection provides multiple quantization levels optimized for cross-platform performance, offering advanced reasoning capabilities with 128k context support.
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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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| **Phi-3.5-mini-instruct-Platinum-F16.gguf** | FP16 | ~7.6 GB | 100% | Master Reference / Benchmarking |
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| **Phi-3.5-mini-instruct-Platinum-Q8_0.gguf** | Q8_0 | ~4.1 GB | 99.9% | Platinum Reference / High-Fidelity |
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| **Phi-3.5-mini-instruct-Platinum-Q6_K.gguf** | Q6_K | ~3.1 GB | 99.8% | High-Quality Inference |
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| **Phi-3.5-mini-instruct-Platinum-Q5_K_M.gguf** | Q5_K_M | ~2.8 GB | 99.4% | Balanced Desktop Performance |
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| **Phi-3.5-mini-instruct-Platinum-Q4_K_M.gguf** | Q4_K_M | ~2.4 GB | 98.8% | Mobile / Low-Power Efficiency |
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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="Phi-3.5-mini-instruct-Platinum-Q8_0.gguf",
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n_gpu_layers=-1, # Target all layers to NVIDIA/Apple GPU
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n_ctx=4096
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)
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output = llm("Discuss the architectural benefits of Phi-3.5.", max_tokens=150)
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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("Phi-3.5-mini-instruct-Platinum-Q8_0.gguf") {
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ContextSize = 4096,
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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("Universal Engine 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:** Phi-3.5
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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 the production line for high-fidelity models requires significant hardware resources. If these tools power your research or industrial projects, 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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4
requirements.txt
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requirements.txt
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optimum-intel[openvino,nncf]>=1.20.0
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transformers>=4.45.0
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accelerate
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sentencepiece
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