# Downstream task fine-tuning

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

This is a transformers model hosted on Hugging Face Hub. Specific functions and uses need to be supplemented.

This is a transformers model hosted on the Hugging Face Hub. Specific functionalities and uses require further 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 Hugging Face Hub, with no specific functionality or purpose clearly stated.

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

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 no specific functionality or purpose clearly stated.

This is a transformers model pushed to the Hugging Face Hub. The specific functions and detailed information are to be supplemented.

TinyMistral-248M is a small language model based on pre-training from the Mistral 7B model, with parameters scaled down to approximately 248 million, primarily used for fine-tuning downstream tasks.

This is a Serbian (Cyrillic and Latin scripts) RoBERTa model pretrained on srWaC, suitable for downstream task fine-tuning.

This is a RoBERTa model pretrained on the CC-100 dataset, suitable for Belarusian text processing tasks.

ALBERT Small v2 is a 6-layer lightweight version of ALBERT-base-v2, based on the Transformer architecture, suitable for natural language processing tasks.

ALBERT XXLarge v2 is a large language model pre-trained with masked language modeling objectives, featuring a parameter-shared Transformer architecture with 12 repeated layers and 223 million parameters.

This is a RoBERTa model pre-trained on Thai Wikipedia text, using character-level embeddings to adapt to BertTokenizerFast.

A small Japanese RoBERTa model pre-trained on Aozora Bunko texts, suitable for various downstream NLP tasks

A RoBERTa model pretrained on Aozora Bunko texts using a character tokenizer, suitable for Japanese text processing tasks.

GPT-Neo 125M is a Transformer model based on the GPT-3 architecture, developed by EleutherAI, with 125 million parameters, primarily used for English text generation tasks.