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.

1. Tailoring Small Language Models
for Enterprise Use Cases
Julien Simon, Chief Evangelist
julien@arcee.ai
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
julien@arcee.ai