108 lines
2.8 KiB
Markdown
108 lines
2.8 KiB
Markdown
---
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license: mit
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datasets:
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- nvidia/Llama-Nemotron-Post-Training-Dataset
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language:
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- en
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- es
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- ar
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- fr
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base_model:
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- ykarout/phi4-deepseek-r1-distilled-v8-GGUF
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- microsoft/phi-4
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library_name: transformers
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tags:
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- deepseek
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- r1
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- reasoning
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- phi-4
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- math
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- code
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- chemistry
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- science
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- biology
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- art
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- unsloth
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- finance
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- legal
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- medical
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- text-generation-inference
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---
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# Phi-4 DeepSeek Distilled v8 GGUF
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This repository contains GGUF quantized versions of the Phi-4 DeepSeek R1 Distilled model. These GGUF files are optimized for local inference using frameworks like [llama.cpp](https://github.com/ggerganov/llama.cpp) and [Ollama](https://ollama.ai/) and LM Studio.
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## Model Information
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- **Base Model**: Phi-4 DeepSeek R1 Distilled
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- **Parameters**: 14.7B
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- **Architecture**: Phi3
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- **Context Length**: 16384 tokens
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- **Training Data**: Improved version of Phi-4, distilled with DeepSeek R1 Reasoning
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- **License**: MIT
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## Available Quantizations
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| File | Quantization | Size | Use Case |
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|------|-------------|------|----------|
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Q8_0
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Q6_K
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Q5_K_M
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Q4_K_M
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## Chat Template
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This model uses the ChatML format with the following structure:
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```
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<|im_start|>system<|im_sep|>System message here<|im_end|>
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<|im_start|>user<|im_sep|>User message here<|im_end|>
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<|im_start|>assistant<|im_sep|>Assistant response here<|im_end|>
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```
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## Usage with Ollama
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Create a custom Modelfile (paste this into a file named `Modelfile`):
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----------------------------------------------------------------------------------
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FROM /replace/with/path/to/your/gguf-file.gguf
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PARAMETER temperature 0.15
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PARAMETER top_p 0.93
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PARAMETER top_k 50
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PARAMETER repeat_penalty 1.15
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TEMPLATE """{{ if .System }}<|im_start|>system<|im_sep|>{{ .System }}<|im_end|>{{ end }}{{ range .Messages }}{{ if eq .Role "user" }}<|im_start|>user<|im_sep|>{{ .Content }}<|im_en>"""
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PARAMETER stop "<|im_start|>"
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PARAMETER stop "<|im_end|>"
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------------------------------------------------------------------------
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Then create and use your model:
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ollama create phi4-deepseek-r1 -f Modelfile
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ollama run phi4-deepseek-r1
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## Usage with LMStudio
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1. Use the model search option to look up the model from huggingface
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2. Download and Load the Model
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3. Set the chat parameters (top_p, top_k, repeat_penalty etc...)
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4. Chat with the model (LMStudio directly detects the chat template so there is no manual configuration here unlike Ollama)
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## Usage with llama.cpp
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```bash
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# Download the model from Hugging Face
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wget https://huggingface.co/ykarout/phi4-deepseek-r1-distilled-v8-GGUF/resolve/main/phi4-deepseek-r1-distilled-v8-q8_0.gguf
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# Run the model with llama.cpp
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./main -m phi4-deepseek-r1-distilled-v8-q8_0.gguf -n 1024 --color -i -ins --chatml
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```
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## Benchmarks & Performance Notes
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- Q8_0: Best quality, requires ~16GB VRAM for 4K context
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- Q3_K_M: Good quality with 60% size reduction, suitable for systems with 8GB+ VRAM |