Meet KwaiAgents: A Generalized Information Search Agent System Based on Large LLM Language Models
Recent advances in the field of artificial intelligence (ai) and Natural Language Processing (NLP) have led to the introduction of ...
Tag: Large
This AI research introduces TinyGPT-V: a parameter-efficient MLLM (Multimodal Large Language Models) designed for a variety of real-world vision language applications.
The development of multimodal large language models (MLLM) represents an important advance. These advanced systems, which integrate language and visual ...
This AI research from China proposes YAYI2-30B: an open source multilingual large language model with 30 billion parameters
Researchers have identified a critical need for models designed specifically for Chinese applications in large language models. The YAYI2-30B model ...
Meet LLM Surgeon: a new machine learning framework for unstructured, semi-structured and structured pruning of large language models (LLM)
Recent advances in artificial intelligence have enabled the development of Large Language Models (LLM) with a significantly large number of ...
Microsoft and Georgia Tech Researchers Introduce VCoder: Versatile Vision Encoders for Multimodal Large Language Models
In the changing landscape of artificial intelligence and machine learning, the integration of visual perception with language processing has become ...
Meet PowerInfer: A fast large language model (LLM) on a single consumer GPU that accelerates machine learning model inference by 11x
Generative large language models (LLMs) are well known for their remarkable performance in a variety of tasks, including complex natural ...
Improved large language models as reasoning engines | by Antonio Alcaraz | December 2023
Recent exponential advances in natural language processing capabilities from large language models (LLMs) have sparked enormous excitement about their potential ...
Understanding LoRA: Low-Range Adaptation for Tuning Large Models | by Bhavin Jawade | December 2023
Mathematics behind this efficient parameter tuning methodFine-tuning large pre-trained models is computationally challenging and often involves tuning millions of parameters. ...
Leveraging Large Language Models to Exploit ASR Uncertainty
With the help of creative engineering and learning in context, large language models (LLMs) are known to generalize well to ...
Training a Large Vocabulary Neural Language Model Using Private Federated Learning for Resource-Constrained Devices
*= Equal taxpayers Federated learning (FL) is a technique for training models using data distributed across devices. Differential Privacy (DP) ...
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