Radal: No-Code Platform for Fine-Tuning Small Language Models
AI Tools & Apps
1
Posts
1
Posters
10
Views
1
Watching
-
Introduction
Radal is a no-code platform designed to fine-tune small language models (SLMs) using your own data. It enables users to connect datasets, configure training visually, and deploy models quickly. Ideal for startups, researchers, and enterprises, Radal eliminates the complexity of MLOps. Visit Radal.
How to Use Radal
Radal provides a visual, no-code interface for training SLMs. Users can:
- Connect datasets
- Drag and drop elements to configure training flows
- Interact with an AI Copilot
- Train models with one click
- Deploy models on edge devices
Core Features
- No-code visual training flow
- AI Copilot for tailored flow construction
- Hugging Face integration for auto-push
- Export quantized models for local/edge deployment
- One-click training and visual iteration
Use Cases
- Industrial IoT: Predictive maintenance using sensor logs for real-time anomaly detection.
- Healthcare: Secure note drafting with HIPAA-compliant on-prem models.
- LegalTech: Drafting motions and surfacing precedents for legal teams.
- EdTech: Offline mobile SLMs for instant homework help.
- SaaS: AI agents for customer support.
- FinTech: Edge models for real-time fraud detection.
FAQ
- What size models can I train with Radal?
- Can I use my own base model?
- What does the Copilot actually do?
- How can I try out my trained model?
- Why even build this? Don’t LLMs already do everything?
- When can I try it out?
For more information, visit Radal's website.