3/ It's not about the volume of data, but diversity and quality—and getting & maintaining this kind of quality dataset takes work. More on this in the “Quality is all you need” section of the Llama-2 paper.
DATA
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Fine-tuning Llama 2: Automating Data Labeling and Curation
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4/ Finally, how do you actually fine-tune Llama 2 for your specific data & objectives? That’s where the data labeling, curation, and development is the hard part. We’re turning this painful manual process into a rapid, iterative, programmatic one like software development.
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Specialist LLM Fine-Tuning Service Offering Available
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5/ If you’re interested in creating a specialist LLM fine-tuned on your data, let’s talk!
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Llama 2 Release Emphasizes Data Quality for LLM Fine-tuning
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Yesterday’s Llama 2 release further highlights the criticality of data quality at all stages of LLM fine-tuning. And we’re excited to support this with solutions for programmatic data development. (1/5)
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Fine-tuned specialist models drive real enterprise AI adoption
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2/ As many enterprises are finding out, real AI use cases often require specialist models fine-tuned on domain-specific data, and tunable “base” models like Llama 2 are the foundation for this.
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Transform Your Organization into an AI-First Company with Our Platform
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You can turn your organization into an AI-first company, We built the world's ONLY AI-assisted data science and MLOps platform.
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Databricks acquires MosaicML to advance generative AI
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Welcome to Databricks, @MosaicML
! #GenerativeAI will drive the next enterprise #data app wave — and we’re excited to work together to accelerate developments and make generative AI accessible to all organizations. Hear what's next from our founders! -
Modern Columnar Data Format for ML and LLMs in Rust
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Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. https://
bit.ly/3NwSGek #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Autonomize AI: Smart Vector Embeddings for Healthcare Domain Retrieval
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Case in point: At Autonomize AI we use smarter ways (use vector embeddings + smaller (healthcare) domain trained models for retrieval augmentation) because at the end of the day for search/IE/business use cases, relevance and accuracy is paramount. Our customers love it!
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Generative AI Data Causes Model Autophagy Disorder MAD
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Generative AI generated data can make #GenerativeAI models go MAD (Model Autophagy Disorder) – super cool paper to review: https://
lnkd.in/gN8QuxW7. It underscores the importance of Data and domain expertise in the age of #AI.