# Low perplexity

GGUF-v3 version file of the Chinese LLaMA-2-7B model adapted to llama.cpp

A 1.3B-parameter language model specifically designed for Uzbek, deeply fine-tuned based on mGPT-XL (1.3B)

Mongolian mGPT 1.3B is a language model with 1.3 billion parameters specifically designed for Mongolian, supporting natural language processing tasks related to Mongolian.

mGPT 13B is a multi-language language model that supports 61 languages, covering 25 language families. It is trained on 600GB of text data and has powerful multi-language processing capabilities.

Thai causal language model based on GPT-2 architecture, trained on the OSCAR dataset

This is a Spanish GPT-2 model trained from scratch on the large_spanish_corpus (BETO corpus) using the Flax framework, developed with support from the HuggingFace community week event.

A GPT-2 language model trained on Ukrainian novels with 124M parameters, specialized for Ukrainian text generation

The first and only available subword BERT model for Ancient Greek, achieving state-of-the-art fine-tuned performance in part-of-speech tagging and morphological analysis tasks.

This is a GPT2 large model (762 million parameters) trained from scratch, focusing on Dutch language, with a perplexity of 15.1 on the clean Dutch mC4 dataset.

A text processing model fine-tuned based on bert-base-uncased, trained on an unknown dataset, with a validation loss of 2.4969 and perplexity of 12.14

This is a fine-tuned version of the GPT2-Small English model, trained on Turkish Wikipedia articles, suitable for Turkish text generation tasks.

Bengali GPT-2 model based on mC4 dataset for text generation tasks

A 345 million parameter GPT-2 model pre-trained on massive Finnish text, excelling in Finnish text generation