What size models can I train with Radal?

The website lists examples of fine-tuning 3-B, 7-B, 5-B, and 4-B models, indicating support for various small language model sizes. Specific limits are not detailed.

Can I use my own base model?

The provided content does not explicitly state whether users can bring their own base models, but it focuses on fine-tuning existing small language models.

What does the Copilot actually do?

The Interactive AI Layer, or AI Copilot, helps users by constructing a tailored training flow for them.

How can I try out my trained model?

Trained models can be tried out locally and can run on edge-devices for continued inference. The website also mentions rapid deployment workflows for LM Studio and PocketPal.

Why even build this? Don’t LLMs already do everything?

The website emphasizes the future of Small Language Models (SLMs) and provides use cases where domain-specific small models can outperform general-purpose giants, such as a fine-tuned LLaMA-8B beating GPT-4 in biomedical questions.

When can I try it out?

Radal is currently in Beta (v0) and encourages users to 'Try Now' or 'Join the waitlist'.

Radal: No-code platform for fine-tuning small language models.

Name: Radal
Rating: 5 (68 reviews)
Author: toolify

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Introduction:

No-code platform for fine-tuning small language models.

Added on:

Aug 04 2025

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Radal Product Information

What is Radal?

Radal is a no-code platform to fine-tune small language models using your own data. It allows users to connect datasets, configure training visually, and deploy models in minutes. The platform is built for startups, researchers, and enterprises needing custom AI without MLOps complexity.

How to use Radal?

Radal simplifies the process of training small language models through a visual, no-code interface. Users can connect datasets, drag and drop elements to configure training flows, and interact with an AI Copilot. Models can be trained with one click, iterated visually, and deployed quickly, even on edge devices.

Radal's 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

Radal's Use Cases

Industrial IoT: Predictive Maintenance (fine-tune edge models on sensor logs for real-time anomaly detection and reduced downtime)

Healthcare: On-Prem Privacy (fine-tune clinical models on patient data for secure note drafting within hospital networks, meeting HIPAA requirements)

LegalTech: Legal Teams (fine-tune legal models on firm’s data to draft motions, surface key precedents, and save attorney time)

EdTech: Offline Mobile (train on-device SLMs with curriculum content for instant homework help without internet connectivity)

SaaS: Customer Support (fine-tune models on support tickets and FAQ docs to create AI agents for routine questions)

FinTech: Edge Payments (fine-tune edge models on transaction logs for real-time fraud detection on card terminals)

FAQ from Radal

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?

Radal Support Email & Customer service contact & Refund contact etc.

More Contact, visit the contact us page(https://radal.ai/#contact)
Radal Company

Radal Company name: Radal AI .
Radal Login

Radal Login Link: https://app.radal.ai

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