# Pre-trained models

This is a transformers model published on the Hugging Face Hub. Specific information is to be supplemented.

This is a transformers model hosted on Hugging Face Hub, with its specific functions and purposes not clearly stated.

AMRBART is a pre-trained semantic parser capable of converting sentences into Abstract Meaning Representation (AMR) graphs. The latest version, v2, is simpler, faster, and more powerful.

This model is based on the transformers library, and its specific functions and uses require further information to be supplemented.

A PyTorch-based semantic segmentation model that supports various encoder architectures, suitable for image segmentation tasks.

This is a transformers model hosted on Hugging Face Hub, with no specific functionality explicitly stated.

This is a transformers model hosted on Hugging Face Hub. Specific functions and purposes require additional information

This is a transformers model hosted on Hugging Face Hub. Specific functions and uses require further information.

This is a transformers model hosted on the Hugging Face Hub. Specific functionalities and uses require further information.

This model is based on the transformers library, but its specific purpose and functionality are not clearly stated.

This is a transformers model hosted on Hugging Face Hub, with no specific functionality or purpose clearly stated.

This is a transformers model hosted on Hugging Face Hub. Specific functions and uses require further information.

This is a transformers model hosted on Hugging Face Hub, with specific functionalities and uses to be supplemented.

This is a transformers model hosted on Hugging Face Hub, with no specific functionality or purpose clearly stated.

This model is based on the Transformers library, and its specific purpose and functionality require further information to determine.

A zero-shot classification model based on the Transformers library, capable of performing classification tasks without task-specific training data.

This is a transformers model hosted on the Hugging Face Hub, with its specific functions and uses not clearly stated.

A pre-trained T5 model optimized for Portuguese, based on continued training from Google's original t5-small checkpoint

This model is based on the transformers library, and its specific purpose and functionality require further information to determine.

This model is based on the transformers library, and its specific purpose and functionality require further information.

This model is based on the transformers library, and its specific purpose and functionality require further information for confirmation.

A zero-shot classification model based on the Transformers library, supporting English text classification tasks.

YOLOv8s is a lightweight object detection model based on Ultralytics' YOLOv8 architecture, suitable for real-time object detection tasks.

This is a basic model card template used to showcase the fundamental information structure of a new model.

WSPAlign is a pre-trained model for word alignment based on large-scale weakly supervised span prediction, supporting word alignment tasks across multiple languages.

BERT (Bidirectional Encoder Representations from Transformers) is a pre-trained language model based on the Transformer architecture, developed by Google.

ViT5-base is a Transformer-based pre-trained encoder-decoder model for Vietnamese, supporting various text generation tasks.

BARThez is a pre-trained French sequence-to-sequence model, specifically optimized for French text processing tasks.

Lawformer is a pre-trained language model designed for Chinese legal long documents, specifically tailored for processing legal texts.