Qwen-SEA-LION-v4-4B-VL is a vision-language model with 4 billion parameters built on the Qwen3-VL-4B-Instruct architecture. It has been specifically instruction fine-tuned for the Southeast Asian region, possessing multilingual and multicultural capabilities, supporting English and seven Southeast Asian languages, and retaining strong vision-language understanding capabilities.

MultimodalTransformersMultiple Languages

This is an optimized version based on the original DeepSeek-OCR model, specifically an OCR model that supports inference on Apple Metal Performance Shaders (MPS) and CPU. It can extract text from images and convert it into a structured format, supporting multilingual document recognition.

MultimodalTransformersOther

GigaChat3-10B-A1.8B is a dialogue model in the GigaChat series, based on the Mixture of Experts (MoE) architecture, with a total of 10 billion parameters, of which 1.8 billion are active parameters. This model uses multi-head latent attention and multi-token prediction technologies, supports a long context of 256,000 tokens, and performs excellently in multilingual dialogue and reasoning tasks.

Natural Language ProcessingSafetensorsMultiple Languages

Qwen3-32B is the latest generation of large language models in the Qwen series, with powerful reasoning, instruction-following, intelligent agent interaction, and multilingual processing capabilities. It supports over 100 languages and dialects and can seamlessly switch between thinking and non-thinking modes, providing users with a natural and smooth dialogue experience.

Natural Language ProcessingTransformers

Chonky is a multilingual paragraph segmentation model based on DistilBERT, fine-tuned on nearly 11 billion tokens from over 34 million Wikipedia articles. It can segment any natural language text into semantic chunks and supports 104 languages.

Natural Language ProcessingTransformersMultiple Languages

Parrotlet-e is an advanced multilingual medical embedding model optimized specifically for medical terms in various Indian languages. It is fine - tuned based on BAAI/bge - m3 and trained on over 18 million pairs of multilingual medical terms. It supports 12 Indian languages and English and has strong robustness against abbreviations, spelling variations, and colloquial expressions in clinical documents.

Natural Language ProcessingTransformers

This is a static quantized version of the yanolja/YanoljaNEXT-Rosetta-27B-2511 model, providing weight files of various quantization types and supporting multilingual translation tasks. The model is specifically optimized for 32 languages, including major languages such as Chinese, English, Japanese, and Korean.

Natural Language ProcessingTransformersMultiple Languages

This project provides a GGUF quantized version of the `yanolja/YanoljaNEXT-Rosetta-4B-2511` model. This model is a large language model focused on multilingual translation tasks, supporting 33 languages including Chinese, English, Japanese, Korean, French, German, etc. The quantized version was created by mradermacher, offering a variety of quantization options with different precisions and file sizes, facilitating deployment and use in resource-constrained environments.

Natural Language ProcessingTransformersMultiple Languages

This is a statically quantized version of the Qwen3-VL-8B-Abliterated-Caption-it model, supporting multilingual image captioning tasks and offering multiple quantization levels to balance performance and resource requirements.

MultimodalTransformersMultiple Languages

Lamapi/next-12b is a large language model based on 12B parameters. It is fine-tuned with a multilingual dataset, supports more than 50 languages, has efficient text generation capabilities, and is suitable for natural language processing tasks in multiple fields such as chemistry, code, biology, finance, and law.

Natural Language ProcessingTransformersMultiple Languages

Lamapi/next-12b is a multilingual large language model with 12 billion parameters, offering multiple quantized versions and supporting various natural language processing tasks such as text generation, question answering, and chatting. This model is trained on multiple domain datasets and features high efficiency and lightweight characteristics.

Natural Language ProcessingTransformersMultiple Languages

Granite-4.0-H-350M-Base is a lightweight decoder-only language model developed by IBM, designed for resource-constrained devices, supporting multilingual text generation and code completion functions.

Natural Language ProcessingTransformers

Next 12B is a multimodal vision-language model with 12 billion parameters based on Gemma 3. It is the most advanced open-source vision-language model in Turkey. This model performs excellently in text and image understanding, with advanced inference and context-aware multimodal output capabilities. It specifically provides professional-level Turkish language support and also has extensive multilingual capabilities.

MultimodalTransformersMultiple Languages

DeepSeek-OCR-8bit is an MLX format version converted from the DeepSeek-OCR model. It is a visual language model specifically optimized for Apple chips, supporting multilingual OCR recognition and image text understanding tasks.

MultimodalMlxOther

This model is a vision-language model in MLX format converted from DeepSeek-OCR, specifically designed for optical character recognition (OCR) tasks. It supports multilingual text recognition and image understanding.

MultimodalMlxOther

This is a multimodal model that supports multilingual processing, covering multiple fields such as natural language processing, code processing, and audio processing. It can perform various tasks such as automatic speech recognition, speech summarization, speech translation, and visual question answering.

MultimodalSafetensorsMultiple Languages

Svara-TTS is an open-source multilingual text-to-speech model for Indian languages, supporting 19 languages (18 Indian languages + Indian English). This model is built based on the Orpheus-style discrete audio token method, aiming to achieve clear, expressive, and low-latency speech synthesis on ordinary GPUs/CPUs.

Audio ProcessingTransformersMultiple Languages

This is an MLX format model converted from the DeepSeek-OCR model, supporting multilingual image text recognition and text generation functions, specifically optimized for OCR tasks.

MultimodalMlxOther

A dedicated novel writing model fine-tuned based on the command-a-03-2025-uncut model, trained with a high-quality novel paragraph dataset, supporting multilingual novel writing tasks

Natural Language ProcessingTransformersMultiple Languages

This is a static quantized version of the PRIME-RL/P1-30B-A3B model, a large language model with 30 billion parameters, optimized specifically for fields such as physics, reinforcement learning, and competition reasoning, and supports English and multilingual processing.

Natural Language ProcessingTransformersMultiple Languages