Search Results for "llm"
Enhancing LLM Tool-Calling Performance with Few-Shot Prompting
LangChain's experiments reveal how few-shot prompting significantly boosts LLM tool-calling accuracy, especially for complex tasks.
Codestral Mamba: NVIDIA's Next-Gen Coding LLM Revolutionizes Code Completion
NVIDIA's Codestral Mamba, built on Mamba-2 architecture, revolutionizes code completion with advanced AI, enabling superior coding efficiency.
AMD Instinct MI300X Accelerators Boost Performance for Large Language Models
AMD's MI300X accelerators, with high memory bandwidth and capacity, enhance the performance and efficiency of large language models.
LangSmith Introduces Flexible Dataset Schemas for Efficient Data Curation
LangSmith now offers flexible dataset schemas, enabling efficient and iterative data curation for LLM applications, as announced by LangChain Blog.
LangSmith Enhances LLM Apps with Dynamic Few-Shot Examples
LangSmith introduces dynamic few-shot example selectors, allowing for improved LLM app performance by dynamically selecting relevant examples based on user input.
NVIDIA TensorRT-LLM Boosts Hebrew LLM Performance
NVIDIA's TensorRT-LLM and Triton Inference Server optimize performance for Hebrew large language models, overcoming unique linguistic challenges.
Circle and Berkeley Utilize AI for Blockchain Transactions with TXT2TXN
Circle and Blockchain at Berkeley introduce TXT2TXN, an AI-driven tool using Large Language Models to simplify blockchain transactions through intent-based applications.
LangGraph v0.2 Enhances Customization with New Checkpointer Libraries
LangGraph v0.2 introduces new checkpointer libraries, including SQLite and Postgres options, to enhance customization and resilience in LLM applications.
NVIDIA Unveils Pruning and Distillation Techniques for Efficient LLMs
NVIDIA introduces structured pruning and distillation methods to create efficient language models, significantly reducing resource demands while maintaining performance.
Anyscale Explores Direct Preference Optimization Using Synthetic Data
Anyscale's latest blog post delves into Direct Preference Optimization (DPO) with synthetic data, highlighting its methodology and applications in tuning language models.
Understanding Decoding Strategies in Large Language Models (LLMs)
Explore how Large Language Models (LLMs) choose the next word using decoding strategies. Learn about different methods like greedy search, beam search, and more.
Strategies to Optimize Large Language Model (LLM) Inference Performance
NVIDIA experts share strategies to optimize large language model (LLM) inference performance, focusing on hardware sizing, resource optimization, and deployment methods.