Qwen2.5-14B-Instruct is a multilingual large language model based on the Qwen2.5 architecture, with 14 billion parameters. It supports 13 languages and has excellent instruction-following and dialogue capabilities. This model performs well in various language tasks and is suitable for text generation and understanding in multilingual scenarios.

Natural Language ProcessingTransformersMultiple Languages

Qwen2.5-14B-Instruct is a large language model with 14 billion parameters, designed specifically for chat and text generation scenarios. This model is built based on the transformers library and is suitable for internal testing and lightweight application deployment.

Natural Language ProcessingTransformersEnglish

Datarus-R1-14B-Preview is an open-source language model based on 14 billion parameters, fine-tuned on the basis of Qwen2.5-14B-Instruct. This model is specifically designed as a virtual data analyst and a solver for graduate-level problems, capable of learning from complete analysis trajectories, including reasoning steps, code execution, error tracking, and final conclusions.

Natural Language ProcessingTransformersEnglish

OpenReasoning-Nemotron-14B is a large language model based on Qwen2.5-14B-Instruct, specifically post-trained for generating solutions in mathematics, code, and science. It performs excellently in multiple reasoning benchmark tests and supports the GenSelect mode to improve performance.

Natural Language ProcessingTransformersMultiple Languages

OpenReasoning-Nemotron-14B is a large language model developed based on Qwen2.5-14B-Instruct, focusing on mathematics, code, and scientific reasoning, and supporting a context length of 64K tokens.

Natural Language ProcessingTransformersMultiple Languages

OpenCodeReasoning-Nemotron-14B is a large language model based on Qwen2.5-14B-Instruct with post-training, specifically optimized for code generation and reasoning, supporting a 32K token context length.

Natural Language ProcessingGgufMultiple Languages

This model is a text generation model fine-tuned based on Qwen2.5-14B-Instruct and trained using the TRL library.

Natural Language ProcessingTransformers

Qwen2.5-14B-Instruct is a 14 billion parameter instruction fine-tuned large language model based on the Qwen2.5 architecture, optimized on the s1K dataset.

Natural Language ProcessingTransformers

Qwen2.5-14B-Instruct-1M is an instruction-tuned model based on Qwen2.5-14B, supporting text generation tasks and suitable for chat scenarios.

Natural Language ProcessingGgufEnglish

Qwen2.5-14B-Instruct is an instruction-tuned model based on Qwen2.5-14B, supporting text generation tasks and suitable for chat and Q&A scenarios.

Natural Language ProcessingGgufEnglish

T3Q-qwen2.5-14b-v1.2-e2 is a post-trained version based on the Qwen/Qwen2.5-14B-Instruct-1M model, using LoRA-8-4-0.0001-cosine-32-16 configuration and trained on train_data_v1.2.

Natural Language ProcessingTransformersMultiple Languages

This is a quantized model based on Qwen2.5-14B-Instruct-1M, converted to GGUF format, suitable for the llama.cpp framework.

Natural Language ProcessingGgufMultiple Languages

A post-trained version based on the Qwen/Qwen2.5-14B-Instruct-1M model, using LoRA-8-4-0.0001-cosine-32-16 configuration, trained on train_data_v1.0.

Natural Language ProcessingTransformersMultiple Languages

Qwen2.5-14B-it-restore is a model generated by combining the della, ties, and model stock fusion methods based on the Qwen2.5-14B and Qwen2.5-14B-Instruct models, aiming to address the decline in instruction-following capability and weakened mathematical ability.

Natural Language ProcessingSafetensorsMultiple Languages

This is a quantized version based on the Qwen2.5-14B-Instruct model, specifically designed for citation intent classification tasks.

Natural Language ProcessingGgufEnglish

A citation intent classification model fine-tuned based on Qwen2.5-14B-Instruct, specializing in citation analysis tasks in scientific literature.

Natural Language ProcessingGgufEnglish

Qwen2.5 is the latest series of Tongyi Qianwen large language models, offering basic language models and instruction-tuned models with various parameter scales from 0.5B to 72B. This 0.5B version has significant improvements in knowledge reserve, coding, and mathematical abilities, supporting long contexts and multilingual processing.

Natural Language ProcessingTransformersMultiple Languages

A multi-stage training model based on Qwen2.5-14B and Qwen2.5-14B-Instruct, focusing on text generation and instruction understanding tasks.

Natural Language ProcessingTransformers

ChatTS-14B is a large language model fine-tuned from Qwen2.5-14B-Instruct, specializing in understanding and reasoning about time series data with a focus on morphological and numerical feature analysis.

MultimodalTransformersMultiple Languages

Qwen2.5-Lumen-14B is a text generation model fine-tuned based on Qwen2.5-14B-Instruct, specifically optimized for story writing and role-playing scenarios. The model achieves better instruction following ability through preference fine-tuning and performs excellently in literary creation and dialogue generation.

Natural Language ProcessingTransformersEnglish