# Multilingual Generation

A quantized version of Medra27B, offering multiple quantization types, suitable for multiple fields such as text generation and medical artificial intelligence.

Falcon-H1 is a high-performance hybrid architecture language model developed by TII, combining Transformers with Mamba architecture to support multilingual tasks.

Nous Consilience 40B is a 40-billion-parameter generative text model pretrained from scratch in a decentralized manner, supporting multiple languages and designed to represent the broad spectrum of human creative output.

Falcon-H1 is an efficient hybrid architecture language model developed by TII, combining Transformer and Mamba architectures to support multilingual tasks

XGLM-564M is a multilingual autoregressive language model with 564 million parameters, trained on a balanced corpus of 30 languages totaling 500 billion subwords.

DeepSeek-R1-Distill-Qwen-7B is a distilled model based on Qwen-7B, supporting multiple languages and suitable for text generation tasks.

An elastic model generated by TheStage AI's ANNA, offering multiple optimized versions to adapt to different scenario requirements, supporting multilingual text generation.

Gemma 3 is a lightweight open model series from Google, built on the research and technology used to create Gemini models. The 12B version is an instruction-tuned multimodal model supporting text and image inputs to generate text outputs.

Compressible version of Qwen2.5-7B provided by the ACIP project, supporting dynamic compression rate adjustment while maintaining model performance

Compressible version of Llama-3.1-8B model provided by the ACIP project, supporting dynamic compression rate adjustment while maintaining performance

An elastically optimized version of Meta-Llama-3.1-8B-Instruct, offering model variants with different speed and precision levels, suitable for self-deployment scenarios.

A 17B-parameter multilingual instruction model based on Llama-4, optimized with FP8 quantization to significantly reduce resource requirements

Gemma 3 is a lightweight open-source multimodal model series developed by Google, built on Gemini technology, supporting text and image inputs with text outputs. The 1B version has undergone instruction tuning and quantization-aware training (QAT), making it suitable for deployment in resource-constrained environments.

GLM-4-9B-0414 is a lightweight member of the GLM family with 9 billion parameters, demonstrating outstanding capabilities in mathematical reasoning and general tasks, ranking among the top in open-source models of similar scale.

Gemma is a family of lightweight, cutting-edge open models introduced by Google, built on the same research and technology as the Gemini models. Supports text and image inputs and generates text outputs.

Gemma 3 is a lightweight, cutting-edge open model series from Google, built on the same technology as Gemini, supporting multimodal input (text/image) and text output. The 27B version significantly reduces memory requirements through quantization-aware training.

Llama 4 Maverick is a multimodal AI model released by Meta, supporting text and image understanding. It adopts a Mixture of Experts (MoE) architecture and excels in multilingual text and code generation tasks.

Mistral-7B-Instruct-v0.3 is an instruction-tuned model based on Mistral-7B, supporting multilingual text generation tasks.

Gemma 3 is a lightweight cutting-edge open model family from Google, built on the same research technology as Gemini models. Supports text/image input and text output, offering both pretrained and instruction-tuned weight versions.

Gemma 3 is a lightweight multimodal open model from Google that supports text and image inputs with text outputs, featuring a 128K large context window and support for 140+ languages.

The NVIDIA Nemotron-H-8B-Base-8K is a large language model (LLM) developed by NVIDIA, designed to generate completions for given text fragments. The model adopts a hybrid architecture primarily composed of Mamba-2 and MLP layers, incorporating only four attention layers. It supports a context length of 8K and covers multiple languages including English, German, Spanish, French, Italian, Korean, Portuguese, Russian, Japanese, and Chinese.

Gemma is Google's lightweight cutting-edge open-source model family, built using the same research technology as Gemini models. Gemma 3 is a multimodal model supporting text/image input and text output.

Gemma 3 is a lightweight, advanced open model series launched by Google, built on the same research technology as Gemini, supporting multimodal input and text output.

Gemma-3 is a lightweight multimodal open model launched by Google, supporting text and image inputs to generate text outputs. Built on the research and technology behind the Gemini model, it features a 128K large context window and supports over 140 languages.

Gemma 3 is a lightweight open-source multimodal model from Google, supporting text and image input with text output, featuring a 128K ultra-long context window and support for 140+ languages.

Gemma 3 is Google's lightweight cutting-edge open-source multimodal model supporting image-text input and text output, featuring a 128K context window and 140+ language support.

Gemma 3 is a lightweight open-source multimodal model from Google, supporting text and image inputs with text outputs, featuring a 128K context window and support for 140+ languages.

Gemma is a series of lightweight, cutting-edge open models launched by Google, built on the same research and technology used to create Gemini models.

Gemma is a series of lightweight, advanced open models from Google, built using the same research and technology as the Gemini models.

Gemma is a series of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create Gemini models.

PaliGemma 2 is an upgraded vision-language model released by Google, combining the capabilities of Gemma 2 and SigLIP vision models, supporting multilingual vision-language tasks.

Kraken is a multilingual dynamic routing large language model supporting 8 European languages, jointly developed by Cognitive Computations, VAGO Solutions, and Hyperspace.ai.

llama3-8b-spaetzle-v20 is a model merged from llama3-8b-spaetzle-v13 and llama-3-wissenschaft-8B-v2, supporting English and German, with strong performance on EQ-Bench v2_de.

An 8-billion-parameter instruction-tuned Thai large language model based on the Llama3-8B architecture, supporting Thai and English.

GGUF format version of Vecteus-v1, supporting English and Japanese text generation

Mixtral-8x22B is a pretrained generative sparse mixture of experts model supporting multiple languages.

DictaLM-2.0 is a 7-billion-parameter pretrained generative text model, optimized for Hebrew, based on an improved Mistral-7B architecture

Mixtral-8x22B is a pre-trained generative sparse mixture of experts model released by Mistral AI, supporting multilingual processing.

This is an open-source model based on the Apache-2.0 license; specific functionalities depend on the actual model*

A fine-tuned model based on Hugging Face Transformers library, supporting Tamil summarization and English-Tamil translation tasks.