CodeV is a 7-billion-parameter vision-language model fine-tuned based on Qwen2.5-VL-7B-Instruct. Through two-stage training of supervised fine-tuning (SFT) and reinforcement learning (RL) based on tool-aware policy optimization (TAPO), it aims to achieve reliable and interpretable visual reasoning. It represents visual tools as executable Python code and ensures the consistency between tool usage and question evidence through a reward mechanism, solving the problem of irrelevant tool invocation under high accuracy.

MultimodalTransformersMultiple Languages

Olmo-3-7B-Instruct-AIO-GGUF is a GGUF quantized version based on the Olmo-3-7B-Instruct model developed by the Allen Institute for AI. This is an autoregressive language model with 7 billion parameters, trained on datasets such as Tulu 2 and UltraFeedback through supervised fine-tuning and direct preference optimization, and performs excellently in question-answering and instruction following.

Natural Language ProcessingTransformersEnglish

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-3-7B-Think-DPO is a 7B parameter language model developed by the Allen Institute for AI. It has the ability of long-chain thinking and performs excellently in reasoning tasks such as mathematics and coding. This model has undergone multi-stage training including supervised fine-tuning, direct preference optimization, and reinforcement learning based on verifiable rewards, and is designed specifically for research and educational purposes.

Natural Language ProcessingTransformersEnglish

xLSTM-7b-Instruct is an experimental fine-tuned version based on NX-AI/xLSTM-7b, specifically optimized for instruction-following tasks. This model adds support for chat templates and uses TRL for supervised fine-tuning training, aiming to provide a better conversational interaction experience.

Natural Language ProcessingTransformers

WEBGEN DEVSTRAL IMAGES is an AI model focused on web page generation. It can generate single-page web pages using HTML, CSS, JS, and Tailwind technologies. This project is trained based on custom templates and uses the supervised fine-tuning method, training with a dataset generated by GPT-OSS-120B.

Natural Language ProcessingTransformersEnglish

GLM-4.5-Air is a foundation model for agents launched by Zhipu AI. It adopts a compact design, unifying reasoning, coding, and agent capabilities to meet the complex requirements of agent applications. The model has a moderate number of parameters and superior efficiency. Multiple versions have been open-sourced and can be used for commercial purposes and secondary development.

Natural Language ProcessingTransformersMultiple Languages

TildeOpen LLM is an open-source foundational language model specifically designed to serve underrepresented Nordic and Eastern European languages. Funded by the European Commission and trained on the LUMI supercomputer, this model has 30 billion parameters and addresses the performance gap faced by users of 19 key languages in existing AI systems.

Natural Language ProcessingTransformersMultiple Languages

DINOv3 is a versatile visual foundation model developed by Meta AI. It can outperform specialized models in a wide range of visual tasks without fine-tuning. This model can generate high-quality dense features and performs excellently in various visual tasks, significantly surpassing previous self-supervised and weakly supervised foundation models.

Computer VisionTransformersEnglish

Cthulhu 24B 1.1 GGUF is a large language model fused based on the Mistral Small series of models, integrating 17 different model components. It has the capabilities of creative writing, uncensored dialogue, and rich language interaction. Inspired by the Cthulhu mythos, this model aims to provide a'super fusion' experience that goes beyond the capabilities of a single model.

Natural Language ProcessingTransformersEnglish

TARS-SFT-7B is a security reasoning model based on supervised fine-tuning. It serves as the basic model for reinforcement learning training and is specifically designed to enhance the security of AI systems. This model starts training from Qwen2.5-7B-Instruct and uses the reasoning process as an adaptive defense mechanism to improve the security performance of the model.

Natural Language ProcessingTransformersEnglish

OLMo 2 1B is a post-training variant of the allenai/OLMo-2-0425-1B-RLVR1 model, undergoing supervised fine-tuning, DPO training, and RLVR training, aiming to achieve state-of-the-art performance across multiple tasks.

Natural Language ProcessingTransformersEnglish

A RoBERTa Large fine-tuned model for detecting AI-generated content

Natural Language ProcessingTransformersEnglish

xGen-MM is a series of the latest foundational large multimodal models (LMMs) developed by Salesforce AI Research, building upon the successful design of the BLIP series with foundational enhancements to ensure a more robust and superior model foundation.

MultimodalSafetensorsEnglish

Cymist2-v0.1 is an advanced language model developed by Cypien AI team, specifically optimized for Turkish and English text generation tasks, supporting Retrieval-Augmented Generation (RAG) and Supervised Fine-Tuning (SFT).

Natural Language ProcessingTransformersMultiple Languages

XGen-MM is the latest multimodal large model series developed by Salesforce AI Research. Based on the successful design of BLIP, it achieves a more powerful and superior model architecture through fundamental enhancements.

MultimodalTransformersEnglish

The gpt2-chatbot is a dialogue model obtained through supervised fine-tuning (SFT) on the Deita dataset based on the GPT2-XL architecture, aiming to change a certain decision tendency. This model supports multi-turn dialogue and performs well in text generation tasks, but has limitations in mathematical reasoning.

Natural Language ProcessingTransformers

The 30B-Lazarus Model is an experimental language model that applies LoRA and model fusion, aiming to enhance model characteristics through superposition while avoiding feature dilution effects.

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