VibeThinker-1.5B is a 1.5-billion-parameter dense language model launched by Weibo AI. It is fine-tuned based on Qwen2.5-Math-1.5B and is specifically designed for mathematical and algorithmic coding problems. Trained using the 'Spectrum to Signal Principle' framework, it outperforms larger models in multiple math competition tests. The training cost is approximately $7,800, and it supports an output of up to about 40k tokens.

Natural Language ProcessingTransformersMultiple Languages

VibeThinker-1.5B-GGUF is the GGUF quantized version of the WeiboAI/VibeThinker-1.5B model, quantized by MaziyarPanahi. This model is a text generation model with 1.5B parameters, supporting multiple quantization levels (from 2-bit to 8-bit), which facilitates efficient operation on various hardware.

Natural Language ProcessingGguf

This is the quantized version of WeiboAI/VibeThinker-1.5B, dedicated to making knowledge accessible to everyone. This project provides optimized model weights, making the model easier to deploy and use.

Natural Language ProcessingGguf

A Chinese text classification model fine-tuned on the Weibo 100k sentiment analysis dataset based on bert-base-chinese

Natural Language ProcessingTransformersChinese

A Chinese named entity recognition model based on the BERT-BiLSTM-CRF architecture, fine-tuned on the Weibo dataset, suitable for entity recognition tasks in social media texts

Natural Language ProcessingTransformers