This is a video understanding model fine-tuned on an unknown dataset based on the VideoMAE-base architecture, specifically designed for sign language recognition tasks. The model achieved an accuracy of 18.64% after 20 training epochs.

Computer VisionTransformers

This model is obtained through distillation training using the high-reasoning-difficulty Gemini 3 Pro preview dataset based on the Qwen3-4B-Thinking-2507 base model. It focuses on improving complex reasoning abilities in the fields of coding and science. Through training with specific datasets, it aims to efficiently transfer the reasoning abilities of large models (such as Gemini 3 Pro) to a smaller-scale model.

Natural Language ProcessingTransformers

This is a video understanding model fine-tuned on an unknown dataset based on the MCG-NJU/videomae-base model. After 20 epochs of training, it achieved an accuracy of 13.31% on the evaluation set. This model is specifically optimized for video analysis tasks.

Computer VisionTransformers

This is a video action recognition model fine-tuned on the WLASL dataset based on the VideoMAE-Base architecture. After 200 epochs of training, it achieved a top-1 accuracy of 52.96% and a top-5 accuracy of 79.88% on the evaluation set, specifically designed for sign language action recognition tasks.

Computer VisionTransformers

This is a text generation model that is specifically fine-tuned based on the Google Gemma-3 model. After training, it can use external tools to generate step-by-step plans. This model is trained on the rewoo/planner_instruction_tuning_2k dataset and uses LoRA technology for efficient fine-tuning.

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

Discord-Hermes-3-8B is a large language model fine-tuned based on NousResearch/Hermes-3-Llama-3.1-8B, specifically optimized for conversation scenarios. Through training on a carefully curated Discord conversation dataset, it improves conversation ability and the quality of chat interaction.

Natural Language ProcessingTransformers

A speculative decoding model specifically designed for Qwen/Qwen3-8B. It uses the EAGLE-3 algorithm to improve the efficiency and quality of text generation and obtains excellent generalization ability through training on multiple high-quality datasets.

Natural Language ProcessingTransformers

Dimple is the first discrete diffusion multimodal large language model (DMLLM) that combines autoregressive and diffusion training paradigms. After training on the same dataset as LLaVA-NEXT, it outperforms LLaVA-NEXT-7B by 3.9%.

MultimodalTransformersEnglish

A large language model fine-tuned on a specific dataset based on the ByteDance-Seed/Seed-Coder-8B-Base model, supporting long sequence input and efficient training strategies.

Natural Language ProcessingTransformers

OLMo 2 1B DPO April 2025 is a post-trained variant based on the allenai/OLMo-2-0425-1B-SFT model, which has undergone supervised fine-tuning and DPO training on the Tülu 3 dataset. This model performs excellently in various tasks such as mathematical reasoning, code generation, and question answering. It is an open-source language model with 1B parameters.

Natural Language ProcessingTransformersEnglish

XiYanSQL-QwenCoder-2504 is the latest SQL generation model that combines fine-tuning and GRPO training. It combines efficiency and accuracy in SQL generation, supports multiple dialects, and is ready to use out of the box. It performs excellently on different dialects and out-of-domain datasets.

Natural Language ProcessingSafetensorsMultiple Languages

This model is a fine-tuned version of google/gemma-2-9b-it for function calling tasks, with training data entirely manually annotated using the Russian version of the DiTy/function-calling dataset.

Natural Language ProcessingGgufOther

Arsh LLM is an open-source large language model designed for research, pretrained on the olmo mixed dataset using a T4 GPU, with a total training time of approximately 4-5 days.

Natural Language ProcessingPytorch

OLMo 2 1B is the smallest model in the open language model series released by the Allen Institute for Artificial Intelligence, based on OLMo-mix-1124 pre-training and further trained with the Dolmino-mix-1124 dataset during the intermediate training phase.

Natural Language ProcessingTransformersEnglish

TinyLLaVA-Video-R1 is a video-text-to-text model obtained through cold-start training of TinyLLaVA-Video using 16 manually annotated samples from the NextQA dataset.

MultimodalTransformers

MiniMaid-L2 is a role-play specialized model further optimized from MiniMaid-L1, achieving outstanding performance among 3B-scale models through knowledge distillation and training on a larger dataset.

Natural Language ProcessingTransformersEnglish

A generative model fine-tuned on an unknown dataset. Specific information about the training data and usage is missing.

Natural Language ProcessingTransformers

A language model fine-tuned based on the Transformers library, with unspecified training dataset

Natural Language ProcessingTransformers

High-performance reasoning model built on the OpenThoughts-114k-math dataset and other cognitive enhancement training sets

Natural Language ProcessingTransformersEnglish