MMCU
Chinese language model evaluation
Evaluates the semantic understanding capabilities of large Chinese language models using a multimodal dataset.
MEASURING MASSIVE MULTITASK CHINESE UNDERSTANDING
87 stars
2 watching
12 forks
Language: Python
last commit: 8 months ago Related projects:
Repository | Description | Stars |
---|---|---|
ieit-yuan/yuan2.0-m32 | A high-performance language model designed to excel in tasks like natural language understanding, mathematical computation, and code generation | 180 |
hit-scir/chinese-mixtral-8x7b | An implementation of a large language model for Chinese text processing, focusing on MoE (Multi-Headed Attention) architecture and incorporating a vast vocabulary. | 641 |
fuxiaoliu/mmc | Develops a large-scale dataset and benchmark for training multimodal chart understanding models using large language models. | 84 |
mikegu721/xiezhibenchmark | An evaluation suite to assess language models' performance in multi-choice questions | 91 |
pku-yuangroup/video-bench | Evaluates and benchmarks large language models' video understanding capabilities | 117 |
cluebenchmark/cluepretrainedmodels | Provides pre-trained models for Chinese language tasks with improved performance and smaller model sizes compared to existing models. | 804 |
tencent/tencent-hunyuan-large | This project makes a large language model accessible for research and development | 1,114 |
qcri/llmebench | A benchmarking framework for large language models | 80 |
freedomintelligence/mllm-bench | Evaluates and compares the performance of multimodal large language models on various tasks | 55 |
yunwentechnology/unilm | This project provides pre-trained models for natural language understanding and generation tasks using the UniLM architecture. | 438 |
damo-nlp-sg/m3exam | A benchmark for evaluating large language models in multiple languages and formats | 92 |
brightmart/xlnet_zh | Trains a large Chinese language model on massive data and provides a pre-trained model for downstream tasks | 230 |
cluebenchmark/electra | Trains and evaluates a Chinese language model using adversarial training on a large corpus. | 140 |
shawn-ieitsystems/yuan-1.0 | Large-scale language model with improved performance on NLP tasks through distributed training and efficient data processing | 591 |
yuliang-liu/multimodalocr | An evaluation benchmark for OCR capabilities in large multmodal models. | 471 |