ARC-Hunyuan-Video-7B is a multimodal model developed by Tencent ARC Lab, specifically designed to understand short video content in the real world. It can process visual, audio, and text signals end-to-end, achieving in-depth structured understanding of videos by integrating multimodal clues.

MultimodalTransformers

A model trained through reinforcement fine-tuning based on Qwen 2.5 32B Instruct, specifically designed to solve challenging deductive reasoning problems in the Temporal Clue dataset.

Natural Language ProcessingTransformersEnglish

A lightweight Chinese GPT2 model pre-trained on CLUECorpusSmall, featuring a 6-layer architecture optimized for Chinese text generation tasks

Natural Language ProcessingTransformersChinese

A lightweight Chinese GPT2 model pre-trained on CLUECorpusSmall, featuring 6-layer/768-dim architecture optimized for Chinese text generation

Natural Language ProcessingTransformersChinese

PromptCLUE is a zero-shot learning framework for full Chinese tasks, pre-trained on billion-scale Chinese corpora, supporting various natural language processing tasks.

Natural Language ProcessingTransformersChinese

A Chinese RoBERTa medium model pre-trained on CLUECorpusSmall, with 8 layers of network and a 512-dimensional hidden layer, suitable for various Chinese NLP tasks.

Natural Language ProcessingJaxChinese

A Chinese RoBERTa model pre-trained on CLUECorpusSmall, with a parameter scale of 8 layers and 512 hidden units, supporting masked language modeling tasks.

Natural Language ProcessingJaxChinese

A Chinese RoBERTa model pre-trained on CLUECorpusSmall, with a parameter scale of 8 layers and 512 hidden units.

Natural Language ProcessingJaxChinese

A Chinese tokenized version of the RoBERTa medium model pre-trained on CLUECorpusSmall corpus, with tokenization processing to enhance sequence handling efficiency

Natural Language ProcessingJaxChinese

One of the 24 Chinese RoBERTa model series pre-trained on CLUECorpusSmall, trained using the UER-py framework, supporting masked language modeling and text feature extraction.

Natural Language ProcessingJaxChinese

A Chinese named entity recognition model fine-tuned based on the RoBERTa-Base architecture, specifically optimized for the CLUENER2020 dataset

Natural Language ProcessingJaxChinese

A lightweight Chinese GPT2 model pre-trained on CLUECorpusSmall, with 6 layers/768 hidden units, suitable for Chinese text generation tasks

Natural Language ProcessingJaxChinese

A Chinese RoBERTa model pretrained on CLUECorpusSmall, with 8 layers and 512 hidden units, suitable for various Chinese NLP tasks.

Natural Language ProcessingJaxChinese

A Chinese word-level RoBERTa medium model pretrained on CLUECorpusSmall, outperforming character-level models in multiple tasks

Natural Language ProcessingJaxChinese

A Chinese RoBERTa model pre-trained on CLUECorpusSmall, featuring 8 layers and 512-dimensional hidden layers, suitable for various Chinese NLP tasks.

Natural Language ProcessingJaxChinese

Chinese RoBERTa model pre-trained on CLUECorpusSmall, featuring 8 layers and 512 hidden dimensions, suitable for various Chinese NLP tasks.

Natural Language ProcessingJaxChinese

Chinese RoBERTa model pretrained on CLUECorpusSmall with 8 layers and 512 hidden units, suitable for various Chinese NLP tasks

Natural Language ProcessingJaxChinese

A medium version of the Chinese RoBERTa model series pre-trained by UER-py, trained on CLUECorpusSmall corpus, suitable for various Chinese NLP tasks.

Natural Language ProcessingJaxChinese

Chinese T5 is a series of pre-trained models based on the T5 architecture, specifically designed for Chinese natural language processing tasks. This model adopts a unified text-to-text format and can handle various NLP tasks. It has been pre-trained on the Chinese CLUECorpusSmall dataset.

Natural Language ProcessingTransformersChinese

Chinese GPT2-distil model, pretrained on CLUECorpusSmall dataset, suitable for Chinese text generation tasks

Natural Language ProcessingJaxChinese