--- base_model: - Qwen/Qwen2.5-14B-Instruct - Lambent/qwen2.5-lumen-rebased-14B library_name: transformers tags: - mergekit - merge --- [![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory) # QuantFactory/qwen2.5-reinstruct-alternate-lumen-14B-GGUF This is quantized version of [Lambent/qwen2.5-reinstruct-alternate-lumen-14B](https://huggingface.co/Lambent/qwen2.5-reinstruct-alternate-lumen-14B) created using llama.cpp # Original Model Card # qwenreinstruct This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details Extracted an approximate LoRA of v000000/Qwen2.5-Lumen-14B, rank 128 difference between that and Instruct, and first applied this to Lambent/qwen2.5-14B-alternate-instruct-slerp which had no issues with EQ-Bench. Then, here, re-applied a density and weight of original Instruct which in previous merges gave me no issues with EQ-Bench. This one has EQ-Bench of 77.6713 and no "emotions don't match reference error" (if possibly still one not parsed). This is similar to Lumen and original Instruct and slightly exceeds both (within margin of error). My hope is that it has healed Instruct somewhat and regained its intelligence. ### Merge Method This model was merged using the della merge method using [Lambent/qwen2.5-lumen-rebased-14B](https://huggingface.co/Lambent/qwen2.5-lumen-rebased-14B) as a base. ### Models Merged The following models were included in the merge: * [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: Qwen/Qwen2.5-14B-Instruct parameters: weight: 0.3 density: 0.4 merge_method: della base_model: Lambent/qwen2.5-lumen-rebased-14B parameters: epsilon: 0.05 lambda: 1 dtype: bfloat16 tokenizer_source: base ```