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Model: pravdin/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B-gguf
Source: Original Platform

README.md

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+---
+license: apache-2.0
+tags:
+- text-generation
+- llama.cpp
+- gguf
+- quantization
+- merged-model
+language:
+- en
+library_name: gguf
+---
+
+# merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B - GGUF Quantized Model
+
+This is a collection of GGUF quantized versions of [pravdin/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/pravdin/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B).
+
+## 🌳 Model Tree
+
+This model was created by merging the following models:
+
+```
+pravdin/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B
+├── Merge Method: dare_ties
+├── Gensyn/Qwen2.5-1.5B-Instruct
+└── deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+    ├── density: 0.6
+    ├── weight: 0.5
+```
+
+**Merge Method**: DARE_TIES - Advanced merging technique that reduces interference between models
+
+
+## 📊 Available Quantization Formats
+
+This repository contains multiple quantization formats optimized for different use cases:
+
+- **q4_k_m**: 4-bit quantization, medium quality, good balance of size and performance
+- **q5_k_m**: 5-bit quantization, higher quality, slightly larger size  
+- **q8_0**: 8-bit quantization, highest quality, larger size but minimal quality loss
+
+## 🚀 Usage
+
+### With llama.cpp
+
+```bash
+# Download a specific quantization
+wget https://huggingface.co/pravdin/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B/resolve/main/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B.q4_k_m.gguf
+
+# Run with llama.cpp
+./main -m merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B.q4_k_m.gguf -p "Your prompt here"
+```
+
+### With Python (llama-cpp-python)
+
+```python
+from llama_cpp import Llama
+
+# Load the model
+llm = Llama(model_path="merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B.q4_k_m.gguf")
+
+# Generate text
+output = llm("Your prompt here", max_tokens=512)
+print(output['choices'][0]['text'])
+```
+
+### With Ollama
+
+```bash
+# Create a Modelfile
+echo 'FROM ./merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B.q4_k_m.gguf' > Modelfile
+
+# Create and run the model
+ollama create merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B -f Modelfile
+ollama run merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B "Your prompt here"
+```
+
+## 📋 Model Details
+
+- **Original Model**: [pravdin/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/pravdin/merged-Gensyn-Qwen2.5-1.5B-Instruct-deepseek-ai-DeepSeek-R1-Distill-Qwen-1.5B)
+- **Quantization Tool**: [llama.cpp](https://github.com/ggerganov/llama.cpp)
+- **License**: Same as original model
+- **Use Cases**: Optimized for local inference, edge deployment, and resource-constrained environments
+
+## 🎯 Recommended Usage
+
+- **q4_k_m**: Best for most use cases, good quality/size trade-off
+- **q5_k_m**: When you need higher quality and have more storage/memory
+- **q8_0**: When you want minimal quality loss from the original model
+
+## ⚡ Performance Notes
+
+GGUF models are optimized for:
+- Faster loading times
+- Lower memory usage  
+- CPU and GPU inference
+- Cross-platform compatibility
+
+For best performance, ensure your hardware supports the quantization format you choose.
+
+---
+
+*This model was automatically quantized using the Lemuru LLM toolkit.*