# Multilingual Support

A 12B-parameter multilingual large language model based on llama.cpp quantization, supporting role-play, story creation, and multi-domain professional tasks

This model is based on the Transformers library, and its specific purpose and functionality require further information to confirm.

DMind-1 is a text generation foundation model dedicated to the free dissemination of knowledge.

This is a GGUF format model converted from PocketDoc/Dans-PersonalityEngine-V1.3.0-24b, suitable for various text generation tasks.

Devstral is a large language model agent for software engineering tasks developed by Mistral AI in collaboration with All Hands AI, excelling in exploring codebases with tools, editing multiple files, and driving software engineering agents.

MedGemma-27B-Text-IT is a large language model developed by Google, focusing on text generation tasks in the medical field.

marin-8b-instruct is an 8B-parameter-scale instruction fine-tuned language model suitable for text generation tasks.

InternVL3-8B-Instruct is an advanced multimodal large language model (MLLM) that demonstrates exceptional overall performance, with strong multimodal perception and reasoning capabilities.

InternVL3-14B-Instruct is an advanced Multimodal Large Language Model (MLLM) that demonstrates exceptional multimodal perception and reasoning capabilities, supporting various tasks such as tool usage, GUI agents, industrial image analysis, and 3D visual perception.

This is a model based on the Hugging Face Transformers library, optimized using Unsloth. Specific functionalities and use cases require further information.

This model is based on the transformers library, and its specific purpose and functionality require further information for confirmation.

This model is based on the transformers library, and its specific purpose and functionality require further information to determine.

BGE-Code-v1 is an LLM-based code embedding model that supports code retrieval, text retrieval, and multilingual retrieval, excelling in code and text retrieval tasks.

This model is based on the transformers library, and its specific purpose and functionality require further information to determine.

This model is based on the transformers library, and its specific purpose and functionality require further information to determine.

An instruction-tuned model based on the Qwen3-14B architecture, specializing in mathematical reasoning, code generation, and factual accuracy

This model is based on the transformers library, and its specific functions and uses require further information to determine.

This model is based on the transformers library, and its specific purpose and functionality require further information to confirm.

A quantized version of Qwen2.5-VL-7B-Instruct, using llama.cpp for quantization, supporting multimodal tasks such as image-to-text conversion.

This model is based on the Transformers architecture, and its specific functions and uses require further information to determine.

This is a model based on the 🤗 transformers library, optimized using unsloth technology. Specific functions and uses require further information.

This is the quantized version of the nomic-ai/nomic-embed-code model, using llama.cpp for imatrix quantization, suitable for code embedding and feature extraction tasks.

This model is based on the transformers library, and its specific purpose and functionality require further information to determine.

Falcon H1 is a hybrid architecture language model developed by the UAE's Technology Innovation Institute, combining Transformer and Mamba architectures to support multilingual processing

A lightweight version of the Qwen2.5 large language model released by Alibaba PAI, focusing on efficient text generation tasks

Gemma 3 is Google's lightweight open model series based on Gemini technology. The 12B version employs Quantization-Aware Training (QAT) technology, supports multimodal input, and features a 128K context window.

This is a transformers model hosted on Hugging Face Hub. Specific functions and uses require further information.

This is a fine-tuned MBert model optimized for German, focusing on the quality domain, developed by the Multi2ConvAI project.

A logistics domain-specific Bert model developed by the Multi2ConvAI project, optimized for English text

This model is based on the transformers library, and its specific purpose and functionality require further information to determine.

Gemma 3 is a lightweight open model series built by Google based on Gemini technology, supporting multimodal input and text output, featuring a 128K large context window and support for 140+ languages.

This model is based on the Transformers library, and its specific purpose and functionality require further information to determine.

InternVL3 is an advanced multimodal large language model series with powerful multimodal perception and reasoning capabilities, supporting image, video, and text inputs.

InternVL3 is an advanced series of multimodal large language models, demonstrating exceptional multimodal perception and reasoning capabilities, supporting image, video, and text inputs.

This model is based on the transformers library, and its specific purpose and functionality require further information for confirmation.

InternVL3-8B-bf16 is a vision-language model based on MLX format conversion, supporting multilingual image-to-text tasks.

This model is based on the Transformers architecture, and its specific purpose and functionality require further information for confirmation.

This model is based on the Transformers library, and its specific purpose and functionality require further information to confirm.

InternVL3-9B is a multimodal large language model from the InternVL3 series, featuring exceptional multimodal perception and reasoning capabilities. It supports various application scenarios such as tool usage, GUI agents, industrial image analysis, and 3D visual perception.

InternVL3-78B is an advanced multimodal large language model developed by OpenGVLab, demonstrating exceptional comprehensive performance. Compared to its predecessor InternVL 2.5, it possesses stronger multimodal perception and reasoning capabilities, extending its abilities to new domains such as tool usage, GUI agents, industrial image analysis, and 3D visual perception.