# Bilingual Support (Chinese-English)

GLM-Z1-9B-0414 is a 9B-parameter open-source model from the GLM family, specializing in mathematical reasoning and general task capabilities, excelling in resource-constrained scenarios.

Wan2.1 is an open and advanced large-scale video generation model with top-tier performance, capable of running on consumer-grade GPUs and excelling in multitask processing.

Qwen2.5-VL-32B-Instruct is a multimodal vision-language model that supports joint understanding and generation tasks for both images and text.

The GPTQ-Int3 quantized version of Qwen2.5-VL-3B-Instruct, suitable for multimodal image-text processing tasks with reduced VRAM usage and faster inference speed.

This is an unofficial GPTQ-Int3 quantized version based on the Qwen2.5-VL-7B-Instruct model, suitable for multimodal image-text-to-text tasks.

Financial domain-specific language model based on Qwen architecture, fine-tuned with 500k+ financial instructions

This model is converted from BAAI/bge-reranker-large into GGUF format for reranking tasks, supporting both Chinese and English.

The LLaVA-Video model is a 7B-parameter multimodal model based on the Qwen2 language model, specializing in video understanding tasks and supporting 64-frame video input.

MiniCPM-Llama3-V-2_5 is a multimodal visual question answering model based on the Llama3 architecture, supporting both Chinese and English interactions.

Llama-3-Chinese-8B-Instruct-v3 is a Chinese instruction model fine-tuned from multiple hybrid models, suitable for dialogue, Q&A, and similar scenarios.

360VL is an open-source large multimodal model developed based on the LLama3 language model, featuring powerful image understanding and bilingual text support capabilities.

360VL is a multimodal model developed based on the LLama3 language model, featuring powerful image understanding and bilingual dialogue capabilities.

Yi-VL-6B is a multimodal vision-language model developed by 01-AI, supporting both Chinese and English, suitable for tasks like visual question answering.

A Chinese biomedical and general chat model based on Llama3-8B, merging two specialized models using the slerp method

MiniCPM-V 2.0 is a powerful multimodal large language model designed for efficient terminal deployment, built upon SigLip-400M and MiniCPM-2.4B and connected via a perceptual resampler.

A dialogue extraction model fine-tuned based on qwen-1.8, capable of batch extracting summaries and dialogues from novel excerpts

TinyLLaVA is a compact large-scale multimodal model framework focused on vision-language tasks, featuring small parameter size yet excellent performance.

A 7B-parameter large language model based on Llama 2 architecture, optimized through DPO training, supporting Chinese and English text generation

ZhiLu is a financial large language model developed based on Chinese Alpaca2-13B, achieving capability leaps through massive incremental pre-training with Chinese and English corpora and high-quality instruction data alignment, with a focus on enhancing performance in the financial domain.

GLM-2B is a general-purpose language model pre-trained with autoregressive blank filling objectives, supporting various natural language understanding and generation tasks.

This model is a fine-tuned T5-small model based on the HUPD dataset, specifically designed for patent text summarization tasks.