GigaChat3-10B-A1.8B is an efficient dialogue model in the GigaChat series. Based on the Mixture-of-Experts (MoE) architecture, it has a total of 10 billion parameters and 1.8 billion active parameters. It adopts the innovative Multi-head Latent Attention (MLA) and Multi-token Prediction (MTP) technologies, aiming to optimize inference throughput and generation speed. The model is trained on 20T tokens of diverse data and supports 10 languages including Chinese, suitable for dialogue scenarios requiring quick responses.

Natural Language ProcessingGgufMultiple Languages

This model is an MLX format conversion version of the Ministral-3-3B-Instruct-2512 instruction fine-tuning model released by Mistral AI. It is a large language model with a parameter scale of 3B, specifically optimized for following instructions and dialogue tasks, and supports multiple languages. The MLX format enables it to run efficiently on Apple Silicon devices.

Natural Language ProcessingMlxMultiple Languages

This project provides a text generation model fine-tuned based on the Microsoft Phi-3.5-mini-instruct model, which has been converted to the GGUF format and is suitable for the llama.cpp inference framework. The model was fine-tuned on the philschmid/guanaco-sharegpt-style dataset, optimizing its instruction-following and dialogue capabilities, and is suitable for efficient text generation tasks in resource-constrained environments.

Natural Language ProcessingGguf

This is a quantized version of the squ11z1's Hypnos-i1-8B model, which is quantized using the llama.cpp tool and a specific dataset. The model is based on the Llama-3 architecture, offering multiple quantization type options and supporting text generation tasks. It is suitable for various application scenarios such as inference and dialogue.

Natural Language ProcessingGgufEnglish

Qwen3-VL-4B-Instruct is a 4-billion-parameter visual language model launched by Alibaba. It is developed based on the Qwen3 architecture and supports multimodal understanding and dialogue tasks. This model has powerful image understanding and text generation capabilities, and can handle complex visual language interaction scenarios.

MultimodalTransformers

This is a bidirectional autoregressive Transformer model based on the 🤗 Transformers library and has been uploaded to the model hub. The model card is automatically generated by the system, and specific technical details and application information need to be further supplemented.

Natural Language ProcessingTransformers

This is the GGUF quantized version of the ai-sage/GigaChat3-10B-A1.8B-bf16 model, offering a variety of quantization options, from high-precision Q8_0 to extremely compressed smol-IQ1_KT, to meet the deployment requirements under different hardware conditions. This model supports a 32K context length, adopts the MLA architecture, and is optimized for dialogue scenarios.

Natural Language ProcessingGgufOther

This is a statically quantized version of the wexyyyyyy/Ru-Gemma3-1B model, supporting Russian and English, and is specifically designed for dialogue and text generation tasks. The model offers multiple quantized versions suitable for different hardware configurations and performance requirements.

Natural Language ProcessingTransformersMultiple Languages

This model is an 8-bit quantized version converted from allenai/Olmo-3-7B-Instruct, specifically optimized for the Apple MLX framework. It is a large language model with 7 billion parameters, supporting instruction following and dialogue tasks.

Natural Language ProcessingMlxEnglish

Strawberry_Smoothie-TEST is a hybrid model obtained by merging three 12B parameter models using the mergekit tool. It combines the advantages of Unity-12B, Chaos-Unknown-12b, and Smoothie-12B-Model_Stock, aiming to provide better text generation and dialogue capabilities.

Natural Language ProcessingTransformers

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

This is a quantized version of the vanta-research/atom-v1-preview-12b model, offering a variety of quantization types. It is suitable for multiple scenarios such as dialogue, collaboration, and education. This model is based on the Gemma architecture and supports English language processing.

MultimodalTransformersEnglish

atom-v1-preview-12b is a quantized version based on the vanta-research/atom-v1-preview-12b base model, offering multiple GGUF quantization format options, suitable for multiple domains such as dialogue, collaboration, and education.

Natural Language ProcessingTransformersEnglish

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

Dia2 is a streaming dialogue text-to-speech (TTS) model developed by Nari Labs. It supports real-time speech generation and can start generating audio without the full text. It can be adjusted according to the dialogue context to achieve a natural and smooth dialogue experience.

Audio ProcessingSafetensorsEnglish

Dia2 is a streamed dialogue text-to-speech (TTS) model developed by Nari Labs. It supports real-time speech generation and can start generating audio without the need for the complete text. It is specifically designed for natural dialogue scenarios.

Audio ProcessingSafetensorsEnglish

This project is a high-quality HQ4_K quantization of the MiniMax-M2 model, optimized specifically for text generation tasks and particularly suitable for dialogue scenarios. This quantized version does not use imatrix and maintains the model's performance.

Natural Language ProcessingGguf

This model is based on the Kimi-Linear-48B-A3B-Instruct large language model of moonshotai and is converted into an 8-bit quantized version suitable for Apple Silicon chips (MLX framework) using the mlx-lm tool. It is an instruction fine-tuned model with 48B parameters, designed specifically for following human instructions and dialogue interaction.

Natural Language ProcessingMlx

MOSS-TTSD is an open-source bilingual spoken dialogue synthesis model that supports Chinese and English. It can convert two-person dialogue scripts into natural and expressive dialogue voices. It supports voice cloning, and the maximum duration of single-round voice generation can reach 1700 seconds.

Audio ProcessingSafetensorsMultiple Languages

Hebrew_Nemo is a large language model focused on Hebrew processing. It has undergone instruction fine-tuning and supports text generation and dialogue interaction. This version is the GGUF quantized version of the original model, offering multiple quantization levels.

Natural Language ProcessingTransformersMultiple Languages