# Bilingual (Chinese-English)

GLM-4-9B-0414 is a lightweight member of the GLM family with 9 billion parameters, excelling in mathematical reasoning and general tasks, providing an efficient solution for resource-constrained scenarios.

This model is an 8-bit quantized MLX format conversion from THUDM/GLM-4-32B-0414, supporting Chinese and English text generation tasks.

Qwen2.5-7B-YOYO-super is an optimized open-source large language model achieved by merging base models and fine-tuned models, focusing on enhancing instruction-following, mathematical, and coding capabilities.

MixTex base_ZhEn is an image-to-text model supporting both Chinese and English, released under the MIT License.

This is the GPTQ-Int4 quantized version of the Qwen2.5-VL-3B-Instruct model, suitable for multimodal tasks involving image-to-text and text-to-text, supporting both Chinese and English.

Ola-7B is a multimodal language model jointly developed by Tencent, Tsinghua University, and Nanyang Technological University, based on the Qwen2.5 architecture. It supports processing image, video, audio, and text inputs and outputs text.

This is a medical domain Q&A model fine-tuned on DeepSeek-R1, specializing in medical-related text generation tasks.

ARWKV-R1-1B5 is an early preview version of a 7-billion-parameter model based on RNN, trained through three-stage knowledge distillation from DeepSeek-R1-Distill-Qwen-1.5B, with a context length of 2k.

Ola-7B is a multimodal large language model jointly developed by Tencent, Tsinghua University, and Nanyang Technological University. Based on the Qwen2.5 architecture, it supports processing text, image, video, and audio inputs and generates text outputs.

FineMedLM-o1 is a specialized large language model designed for advanced medical reasoning, featuring a multi-step reasoning mechanism that refines and perfects its thought process before delivering a final response.

A multimodal dialogue model fine-tuned based on google/paligemma-3b-mix-448, optimized for multi-turn conversation scenarios

CogVLM2 is a multimodal dialogue model based on Meta-Llama-3-8B-Instruct, supporting both Chinese and English, with 8K context length and 1344*1344 resolution image processing capabilities.

MiniCPM is an edge-side large language model series jointly developed by FaceWall Intelligence and Tsinghua University's Natural Language Processing Laboratory. The core model contains only 1.2 billion non-embedding parameters and outperforms larger open-source models in multiple evaluations.

MiniCPM-V is an efficient lightweight multimodal model optimized for edge device deployment, supporting bilingual (Chinese-English) interaction and outperforming models of similar scale.

Nanbeige 16B Base 32K is a large language model developed by Nanbeige LLM Lab, supporting both Chinese and English with a 32K context length, suitable for various text generation tasks.

A Chinese-English bilingual large language model jointly open-sourced by DeepLang Tech and Tsinghua NLP Lab, pre-trained on trillions of high-quality tokens with 8K context window processing capability

Chinese-LLaMA-2-1.3B is a Chinese foundational model based on Meta's released Llama-2 model, expanded with a Chinese vocabulary and pre-trained in Chinese to enhance basic semantic understanding capabilities in Chinese.

CodeLlama is a model specifically designed for code assistance, excelling in handling programming-related Q&A and supporting multi-turn dialogues in Chinese and English.

A Vicuna fine-tuned dialogue model based on Baichaun-13B-chat, excelling in general conversations and medical consultations.

Ziya Writing Large Model V1 is a 13-billion-parameter instruction fine-tuned model based on LLaMa, specializing in writing tasks such as official documents, speeches, letters, and creative copywriting.

MOSS is an open-source conversational language model supporting plugin enhancement, with 16 billion parameters, capable of Chinese-English dialogue and tool calling.