piccoli_no_style-lora is a generative model based on image-to-video and LoRA technology. It is trained using AI Toolkit and is based on the Qwen/Qwen-Image model. It supports various image generation scenarios.

MultimodalDiffusers

DeepSeek-GRM-16B is a generative reward model based on Self-Principled Critique Tuning (SPCT), which can generate a transparent 'Principle → Critique → Score' evaluation process for query-responses and can be used in tasks such as reinforcement learning, evaluation, and data collection of large language models.

Natural Language ProcessingTransformersMultiple Languages

This is a medical image processing model based on the score-based generative diffusion model, specifically designed for dehazing cardiac ultrasound images. This model is trained on the DehazeEcho2025 dataset and can effectively remove the hazy interference in ultrasound images and improve the image clarity.

Computer VisionTensorflow

A visual motion control model based on the diffusion strategy, which treats robot control as a generative diffusion process and can generate smooth multi-step action trajectories. It performs excellently in rich contact operation tasks.

Computer VisionSafetensors

RedQueen Llama 3.2 3B is a generative Q&A model designed specifically for Sinhala. It uses a two-stage fine-tuning process. First, it builds the language foundation, and then it adapts to the Q&A task. This model performs excellently in Sinhala language understanding and Q&A generation tasks and has 3 billion parameters.

Natural Language ProcessingTransformersOther

Chroma1-Base is a text-to-image basic model with 8.9 billion parameters, built on the FLUX.1-schnell architecture and licensed under the Apache 2.0 license. This model is designed for fine-tuning, providing a powerful and neutral foundation for developers, researchers, and artists to create specialized generative models.

MultimodalDiffusers

Cogito v2 is a generative hybrid inference model fine-tuned by instructions. It uses iterative distillation and amplification training methods and performs excellently in coding, STEM, instruction following, etc. It supports over 30 languages and a 128k context length.

Natural Language ProcessingTransformers

Cogito v2 is a generative large language model fine-tuned with instructions, adopting a mixture-of-experts architecture and having 109 billion parameters. This model supports multilingual processing and long-context reasoning, and performs excellently in fields such as coding and STEM. It supports commercial use.

Natural Language ProcessingTransformers

Cogito v2 is a generative large language model based on instruction tuning, with hybrid reasoning ability, supporting a 128k context length and multilingual processing. This model adopts the Iterative Distillation and Amplification (IDA) training strategy and performs excellently in tasks such as coding, STEM, and instruction following.

Natural Language ProcessingTransformers

Cogito v2 is an instruction-tuned generative model based on Llama-3.1-70B. It has hybrid inference capabilities, supports multiple languages and long contexts, and performs excellently in areas such as coding and STEM. It adopts an iterative distillation and amplification training strategy and can be used for commercial purposes.

Natural Language ProcessingTransformers

Llama-3.1-8B-Instruct-RM-RB2 is one of the reward models released by the Allen Institute for Artificial Intelligence. It is fine-tuned based on Llama-3.1-8B-Instruct and is used to evaluate and optimize the preference learning of generative models.

Natural Language ProcessingTransformersEnglish

ThinkPRM-7B is a generative process reward model based on the R1-Distill-Qwen-7B architecture, specifically designed for step-by-step verification of inference processes. It evaluates the correctness of each step in reasoning tasks such as mathematical problem-solving and code generation by generating explicit verification thought chains, featuring high data efficiency and strong interpretability.

Natural Language ProcessingTransformersOther

Sundial is a series of generative time series foundation models capable of zero-shot inference for both deterministic and probabilistic forecasting.

Scientific ComputingSafetensors

Nous Consilience 40B is a 40-billion-parameter generative text model, pre-trained from scratch in a decentralized manner, supporting multiple languages and representing diverse human creative output.

Natural Language ProcessingSafetensorsMultiple Languages

Mistral-7B-v0.1 is a pre-trained generative large language model with 7 billion parameters, which outperforms the Llama 2 13B model in multiple benchmark tests. It adopts an advanced Transformer architecture design, including Grouped Query Attention and Sliding Window Attention mechanisms.

Natural Language ProcessingPytorchEnglish

Bielik-4.5B-v3 is a Polish generative text model with 4.6 billion parameters, developed by SpeakLeash in collaboration with ACK Cyfronet AGH, trained on a curated Polish corpus.

Natural Language ProcessingTransformersOther

Nous Consilience 40B is a generative text model pretrained in a decentralized manner via the internet, representing the diverse and extensive creative achievements of humanity.

Natural Language ProcessingSafetensorsMultiple Languages

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.

Natural Language ProcessingSafetensorsMultiple Languages

Llama 3.2 is a collection of 1B and 3B parameter-scale multilingual generative models released by Meta, optimized for dialogue scenarios and supporting various language tasks.

Natural Language ProcessingGgufMultiple Languages

ThinkPRM-1.5B is a generative process reward model based on the R1-Distill-Qwen-1.5B architecture, capable of step-by-step verification of reasoning processes by generating verification chains of thought.

Natural Language ProcessingTransformersOther