This project provides a quantized version (Int4) of Qwen/Qwen3-VL-32B-Thinking, aiming to lower the hardware threshold for model deployment and make the knowledge of advanced visual language models accessible to everyone.

MultimodalGguf

Rnj-1-instruct is an 8-billion-parameter open-weight dense model trained from scratch by Essential AI. It is optimized for code, STEM fields, agent capabilities, and tool invocation. It performs excellently in multiple programming languages and also demonstrates strong capabilities in mathematics and science, comparable to the most advanced open-weight models.

Natural Language ProcessingTransformers

VibeThinker-1.5B is a 1.5-billion-parameter dense language model launched by Weibo AI. It is fine-tuned based on Qwen2.5-Math-1.5B and is specifically designed for mathematical and algorithmic coding problems. Trained using the 'Spectrum to Signal Principle' framework, it outperforms larger models in multiple math competition tests. The training cost is approximately $7,800, and it supports an output of up to about 40k tokens.

Natural Language ProcessingTransformersMultiple Languages

Olmo 3 is a series of language models developed by the Allen Institute for AI, including two scales of 7B and 32B, with two variants: instructional and reflective. This model performs excellently in long-chain thinking and can effectively improve the performance of reasoning tasks such as mathematics and coding. It adopts a multi-stage training method, including supervised fine-tuning, direct preference optimization, and reinforcement learning with verifiable rewards.

Natural Language ProcessingTransformersEnglish

Olmo 3 is a series of language models developed by the Allen Institute for AI (Ai2), including two specifications of 7B and 32B, with two variants of Instruct and Think. This model is based on the Transformer architecture and has the ability of long-chain thinking, which can effectively improve the performance of reasoning tasks such as mathematics and coding.

Natural Language ProcessingTransformersEnglish

Olmo 3 is a new family of language models developed by the Allen Institute for AI, including two scales of 7B and 32B, with two variants: Instruction and Think. This model uses long-chain thinking to improve performance in reasoning tasks such as mathematics and coding, aiming to promote the scientific development of language models.

Natural Language ProcessingTransformersEnglish

PokeeResearch - 7B is a 7 - billion - parameter in - depth research agent model developed by Pokee AI. It combines Reinforcement Learning from AI Feedback (RLAIF) and a powerful reasoning framework, enabling reliable, aligned, and scalable research - level reasoning in tool - enhanced large language models. It is suitable for complex multi - step research workflows.

Natural Language ProcessingTransformersEnglish

Bee-8B is an advanced fully open-source multimodal large language model that focuses on data quality and aims to narrow the performance gap with proprietary models. By using the high-quality Honey-Data-15M corpus and the advanced data processing pipeline HoneyPipe, it demonstrates excellent performance in complex reasoning and other aspects.

MultimodalTransformersEnglish

Apertus is a fully open multilingual large language model developed by Swiss AI, offering two parameter scales of 7 billion and 8 billion. This model supports over 1000 languages, uses fully compliant and open training data, and its performance can rival that of closed-source models. Apertus was pre-trained on 15T tokens and adopts a phased curriculum training method, supporting a context length of up to 65,536 tokens.

Natural Language ProcessingTransformersOther

Apertus is a fully open multilingual large language model developed by Swiss AI. It has parameter scales of 8 billion and 70 billion, supports over 1000 languages and long context processing, and only uses fully compliant open training data. Its performance can rival that of closed-source models.

Natural Language ProcessingTransformersOther

CoDA is a code generation language model based on diffusion models developed by Salesforce AI Research. It has the ability to understand bidirectional context and is specifically designed for powerful code generation and completion tasks. This model only has 1.7 billion parameters and achieves excellent code generation performance while maintaining low computational requirements.

Natural Language ProcessingTransformersEnglish

AcTora is an advanced language model and Python library designed to predict user interactions on social media. This project was developed by AmrTweg with the support of RdivxeAI and MechaML, aiming to apply language models to marketing research.

Natural Language ProcessingTransformers

GA Guard Lite is a lightweight open-source moderation model developed by General Analysis, specifically designed to detect prohibited content in the outputs of language models. This model can identify seven categories of security risks, including illegal activities, hate speech, and personal information leakage, providing efficient content security protection for AI applications.

Natural Language ProcessingTransformersEnglish

This is the quantized version of the Tesslate/UIGEN-FX-4B-Preview model, aiming to make large language models easier to deploy and use through quantization technology, realizing the concept of 'Making knowledge accessible to everyone'.

Natural Language ProcessingGguf

Olmo 3 is a new series of 7B parameter language models developed by the Allen Institute for AI. Based on the Transformer architecture, it is trained on the Dolma 3 dataset, aiming to promote the scientific development of language models. The model offers various variants such as Base, Instruct, and Think, supporting a maximum context length of 65,536.

Natural Language ProcessingTransformersEnglish

This is a quantized version based on the Huihui-Hunyuan-MT-Chimera-7B model, aiming to make large language models easier to deploy and use through quantization technology, enabling knowledge to be accessible to everyone.

Natural Language ProcessingGguf

This project provides a quantized version of Tencent's Hunyuan-MT-7B large language model. Through model compression technology, it reduces the computing and storage requirements, aiming to make knowledge accessible to everyone and make high-performance AI models more popular and user - friendly.

Natural Language ProcessingGguf

This is a large language model with 70B parameters merged using the Linear DELLA method. Based on the Llama-3.1-Nemotron-lorablated-70B base model, it integrates multiple high-performance Llama-3.3-70B variant models, aiming to provide more powerful language understanding and generation capabilities.

Natural Language ProcessingTransformers

GLM-4.5V-AWQ-4bit is a quantized multimodal model built on Zhipu AI's next-generation flagship text foundation model. Optimized by AWQ-4bit quantization technology, it significantly reduces the computational resource requirements while maintaining excellent performance. This model achieves SOTA performance among models of the same scale in 42 public visual language benchmark tests and has powerful visual reasoning capabilities.

MultimodalTransformersMultiple Languages

GoldDiamondGold-70b is a large language model merged from multiple pre-trained language models using the mergekit tool. This model adopts the SCE merging method, based on cogito-v2, and integrates 17 different 70B parameter-scale models, aiming to combine the advantages of each model and provide intelligent text generation and dialogue capabilities.

Natural Language ProcessingTransformers