Tailoring Small Language Models for Enterprise Use Cases
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The document outlines the advantages of tailoring small language models for enterprise use, emphasizing ownership, privacy, compliance, and cost-performance optimization. It presents Arcee.ai's innovative tools for model adaptation and demonstrates the effectiveness of their models through various benchmarks. The message encourages businesses to embrace AI solutions and customize them to their specific needs.
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Tailoring Small Language Models for Enterprise Use Cases
- 1. Tailoring Small Language Models for Enterprise Use Cases Julien Simon, Chief Evangelist [email protected] linkedin.com/in/juliensimon youtube.com/juliensimonfr
- 2. Why rent your AI models when you can own them? 🔒 Increase privacy and compliance 👔 Tailor models to your use cases Maximize ROI 📈 Right-size cost-performance 🚗
- 4. Arcee.ai - The Open SLM leader State-of-the-art tailoring stack Spectrum (continuous pre-training), MergeKit (merging), DistilKit (distillation), EvolKit (dataset improvement) Best-in-class models based on open architectures Hugging Face OpenLLM Leaderboard benchmarks Qwen2 72B 🥇 Best Arabic model Llama 3.1 70B 🥇 Best 70B model Qwen2 1.5B 🥇 Best 1.5B model Llama 3.1 8B 🥇 Best 8B model
- 5. A modern model adaptation workflow Pretrained model Domain- adapted model Instruction- tuned model Aligned model Alignment Merging instruction-following behavior Instruction- tuned model Merging domain knowledge Domain- adapted model Merging alignment behavior Aligned model Merging steps can be combined, e.g., merge with a domain-adapted and aligned model 📄📄📄 Unlabeled domain dataset 📄📄📄 Preference dataset 📄📄📄 Q&A dataset Continuous pre-training (CPT) Instruction fine-tuning (IFT) Spectrum DPO LoRA EvolKit
- 6. Try it at supernova.arcee.ai Book a demo at www.arcee.ai/book-a-demo Deploy it in one click on the AWS Marketplace
- 7. Bye bye closed models AI is changing all businesses. Make it yours and own it. Julien Simon, Chief Evangelist [email protected]