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---
library_name: transformers
base_model:
- Qwen/Qwen2.5-7B-Instruct
license: apache-2.0
---
[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
# QuantFactory/Rombos-LLM-V2.5-Qwen-7b-GGUF
This is quantized version of [rombodawg/Rombos-LLM-V2.5-Qwen-7b](https://huggingface.co/rombodawg/Rombos-LLM-V2.5-Qwen-7b) created using llama.cpp
# Original Model Card
# Rombos-LLM-V2.5-Qwen-7b
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/oL_yvvRsWj2C4niGgkT2A.jpeg)
Rombos-LLM-V2.5-Qwen-7b is a continues finetuned version of Qwen2.5-7B. I noticed recently that the Qwen team did not learn from my methods of continuous finetuning, the great benefits, and no downsides of it. So I took it upon myself to merge the instruct model with the base model myself using the *Ties* merge method
This version of the model shows higher performance than the original instruct and base models.
Quants:
GGUF: https://huggingface.co/bartowski/Replete-LLM-V2.5-Qwen-7b-GGUF
Benchmarks: (Coming soon)