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Janus-Pro-1B is an innovative multimodal model focused on unifying multimodal understanding and generation. It solves the conflicting problem of traditional methods in understanding and generation tasks by separating the visual encoding path, while maintaining a single unified Transformer architecture. This design not only improves the model's flexibility but also enables it to perform well in multi-modal tasks, even surpassing task-specific models. The model is built on DeepSeek-LLM-1.5b-base/DeepSeek-LLM-7b-base, uses SigLIP-L as the visual encoder, supports 384x384 image input, and uses a specific image generation tokenizer. Its open source nature and flexibility make it a strong candidate for the next generation of multimodal models.
InternVL 2.5 is a series of advanced multimodal large language models (MLLM) that builds on InternVL 2.0 by introducing significant training and testing strategy enhancements and data quality improvements, while maintaining its core model architecture. The model integrates the newly incrementally pretrained InternViT with various pretrained large language models (LLMs), such as InternLM 2.5 and Qwen 2.5, using randomly initialized MLP projectors. InternVL 2.5 supports multiple image and video data, and enhances the model's ability to handle multi-modal data through dynamic high-resolution training methods.
Molmo is an open, state-of-the-art family of multi-modal AI models designed to enable rich interactions with the physical and virtual world by learning to direct the content of its perception, empowering next-generation applications to act and interact. Molmo enables rich interactions with the physical and virtual world by learning to point to the content it senses, providing next-generation applications with the ability to act and interact.
Unified-IO 2 is a unified multi-modal generative model capable of understanding and generating images, text, audio and motion. It uses a single encoder-decoder Transformer model to represent the input and output of different modes (image, text, audio, action, etc.) into a shared semantic space for processing. The model is trained from scratch on a large-scale multi-modal pre-training corpus and optimized using multi-modal denoising targets. To learn a wide range of skills, the model is also fine-tuned on 120 existing datasets that incorporate hints and data augmentation. Unified-IO 2 achieves state-of-the-art performance on the GRIT benchmark, achieving strong results on more than 30 benchmarks, including image generation and understanding, text understanding, video and audio understanding, and robotic manipulation.
Cerebrium is a machine learning framework that makes it easy to train, deploy, and monitor machine learning models with just a few lines of code. We run everything on serverless CPU/GPU and only charge based on usage. You can deploy models from libraries such as Pytorch, Huggingface, Tensorflow, and more.
Hive AI’s API allows developers to integrate pre-trained AI models into their applications, solving technically challenging content understanding needs. Hive AI provides industry-leading AI models and provides services through APIs to achieve human-level accuracy and machine-level efficiency. Please visit the official website for pricing and positioning information.
Cameralyze is an easy-to-use AI platform that provides multiple pre-built models and a no-code interface to help users seamlessly integrate artificial intelligence into applications and gain a competitive advantage. The platform supports various industries and application scenarios and provides payment plans with transparent pricing.
DirectAI is a platform based on large language models and zero-shot learning that can instantly build a model that suits your needs based on your description, without the need for training data. You can deploy and iterate models in seconds, eliminating the time and expense of assembling training data, labeling data, training the model, and fine-tuning the model. Headquartered in New York City and backed by venture capital, DirectAI is changing the way people use artificial intelligence in the real world.
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