KaniTTS is a high-speed, high-fidelity Arabic text-to-speech model optimized for real-time conversational artificial intelligence applications. It adopts a two-stage pipeline architecture, combining a large language model with an efficient audio codec to achieve excellent speed and audio quality, and can meet the speech synthesis needs of multiple fields such as conversational AI, accessibility assistance, and research.

Audio ProcessingTransformersArabic

This is a quantized version of the afkfatih/LFM2-8B-A1B-TR model, offering various GGUF quantization formats. The model is a multilingual large language model with 8 billion parameters, specifically optimized for the Turkish language and supporting 9 languages including English, Chinese, and Arabic.

Natural Language ProcessingTransformersMultiple Languages

DIMI Arabic OCR v2 is an optical character recognition model specifically optimized for Arabic text recognition. It is developed based on fine-tuning Qwen2.5-VL-7B-Instruct and has significant improvements in handling texts with dense diacritics compared to the v1 version.

MultimodalPeftArabic

An instruction model for Moroccan Arabic (Darija) fine-tuned based on the Gemma-3-1B model, specifically optimized for Q&A tasks in the Moroccan region and capable of effectively understanding and generating Darija content.

Natural Language ProcessingSafetensorsOther

A multilingual text generation model based on the RWKV-7 architecture, with 2.9 billion parameters, supporting multiple languages such as English, Chinese, Japanese, Korean, French, Arabic, Spanish, and Portuguese, using the flash-linear attention format, suitable for high-quality text generation tasks.

Natural Language ProcessingGgufMultiple Languages

rwkv7-7.2B-g0 is a multilingual text generation model with 7.2 billion parameters based on the RWKV7 architecture. It uses innovative quantization optimization techniques, supports multiple languages such as English, Chinese, Japanese, Korean, French, Arabic, Spanish, and Portuguese, and has efficient inference performance and a wide range of application scenarios.

Natural Language ProcessingGgufMultiple Languages

LFM2-1.2B is a multilingual text generation model launched by LiquidAI, supporting multiple languages such as English, Chinese, and Arabic, providing strong support for scenarios like text creation. This model is optimized by MLX and is particularly adapted to Apple Silicon chips.

Natural Language ProcessingTransformersMultiple Languages

FaseehGPT is a GPT-style language model designed specifically for Arabic text processing, optimized for resource-constrained environments, and capable of generating coherent Arabic text.

Natural Language ProcessingTransformersArabic

A Whisper Small model fine-tuned for Arabic recitation of the Quran, capable of accurately identifying and transcribing Quran recitation content.

Audio ProcessingSafetensorsMultiple Languages

An ultra-lightweight Arabic letter recognition model developed by the PaddleOCR team, supporting the recognition of Arabic letters and numeric characters.

Fanar-1-9B-Instruct is a powerful Arabic-English large language model developed by the Qatar Computing Research Institute (QCRI). It supports Modern Standard Arabic and multiple Arabic dialects, and is aligned with Islamic values and Arab culture.

Natural Language ProcessingTransformersMultiple Languages

A multilingual text generation model fine-tuned based on unsloth/Llama-3.3-70B-Instruct-bnb-4bit, supporting English, Spanish, Latin, Arabic, and French.

Natural Language ProcessingTransformersMultiple Languages

A large language model for Arabic logical reasoning fine-tuned based on Qwen3-14B, optimized specifically for enhancing Arabic logical reasoning ability

Natural Language ProcessingTransformersArabic

A large Arabic logical reasoning model fine-tuned based on Qwen3-14B, optimized for Arabic logic and deductive reasoning while retaining general conversational capabilities.

Natural Language ProcessingPytorchArabic

A multilingual dialogue model fine-tuned based on the LLaMA architecture, supporting Arabic and English, optimized for dialogue tasks and providing high-quality responses.

Natural Language ProcessingPytorch

An Arabic text summarization model fine-tuned based on AraT5v2, optimized for news and long-text summarization

Natural Language ProcessingTransformers

Arabic image captioning model fine-tuned based on BLIP architecture, specifically optimized for the Flickr8k Arabic dataset

MultimodalTransformersMultiple Languages

An Arabic dialect classifier fine-tuned based on MARBERTv2, capable of identifying five major Arabic written dialects

Natural Language ProcessingTransformersMultiple Languages

This is an automatic speech recognition model fine-tuned based on the wav2vec2-large-xlsr-53 architecture, specifically optimized for Egyptian Arabic, Modern Standard Arabic, and Gulf/Levantine Arabic. The model is trained on multiple Arabic speech datasets and achieves a word error rate of 27.20% on the Common Voice 17.0 Arabic test set, outperforming many similar models.

Audio ProcessingTransformersMultiple Languages

This is a Whisper-small automatic speech recognition model fine-tuned for Egyptian Arabic dialect, trained based on the SpeechBrain toolkit.

Audio ProcessingTransformersMultiple Languages