Results for “retrieval augmented generation”

…models to perform all of BERT's functions alongside text generation, streamlining model usage across tasks. RAG Strategy for Hybrid Retrieval: A member advocated for a RAG approach with hybrid retrieval, drawing from experience with over…

…fine-tuning can actually introduce new knowledge, acting like retrieval-augmented generation, contrary to widespread assumptions. They linked the Unsloth doc on fine-tuning benefits to address these ongoing misconceptions. Some pointed out …

…with distillation frameworks, citing ollama for synthetic data generation and noting gaps in existing support for these tools. They highlighted Command R as a large language model with 128,000-token context length and retrieval-augmented…

…advancements. Discussion suggested investigating tool augmented generation employing techniques like RAG, API interactions, web searches, and Python executions. DSPy Discord LanceDB Integration PR Submitted: A member raised a PR for LanceDB…

…LLMs, enabling developers and businesses to perform seamless retrieval-augmented generation (RAG) on their own data.: This open-source repository offers reference code for integrating workplace datastores with Cohere's LLMs, enabling…

…graph of user interactions to deliver fast, deterministic fact retrieval. They just released their new community edition; check it out on GitHub! Swyx commentary: The use of Knowledge Graphs for Memory was one of the hottest topics at the…

…with behavioral techniques. LlamaIndex Discord Auto-Document Retrieval Boosts Efficiency: A recent notebook illustrates combining RAG (Retrieval-Augmented Generation) with structured querying, enhancing document retrieval for large…

…(Unsloth AI blog). Dynamic Data Updates in LlamaIndex help keep retrieval-augmented generation systems current using periodic index refreshing and metadata filters in LlamaIndex Guide. AI Video Generation and Vision-LSTM techniques explore …

…Cohere ▷ #cmd-r-bot (9 messages🔥): Command R, Command R+, Retrieval-Augmented Generation Command R Model Overview: Command R is a large language model optimized for conversational interaction and long context tasks, enabling companies to…

…RAG Compute Cost Challenges: Discussions highlighted that retrieval-augmented generation (RAG) can lead to high compute costs due to extensive context length requirements, as outlined in Fine-Tuning or Retrieval? Comparing Knowledge…

…A link was shared to a paper and Twitter post discussing "Retrieval Augmented Fine-Tuning (RAFT)" which aims to make Language Models like Llama 7B more robust by training with distractor documents and incorporating chain-of-thought. The…

…tool lms. LM Studio RAG Feature Improvements: The RAG (Retrieval Augmented Generation) feature has been improved in this version, allowing users to upload documents and ask the LLM questions about them. The RAG feature now uses the Nomic…