EasyLLM

Pipeline

Data

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Finetuning

Closed and Open models

Azure OpenAI

AWS Bedrock

GCP Vertex AI

Google AI Studio

Hyperparameter Tuning

Epoch

Learning Rate

Batch Size

LoRA Rank

Experiment Tracking

Weights And Biases Integration

Data

Models

Config

Evaluation

Classification

Exact Match

Similarity

LLM Judge

Custom

Cut your costs by 200x, still get better performance!

State of the art performance at a fraction of the cost

Achieve better performance with finetuned LLMs than prompt engineering based solutions

Just an excel file is all you need

Finetune LLMs in hours, not months!

Our product simplifies the process of creating and managing finetuned LLMs

Minimal effort, maximum gains

Complete No-Code solution for finetuning LLMs

Built in Versioning, Hyperparameter tuning, Experiment tracking, Evaluations

No more struggling to manage data and models

Improve your models continuously with little effort!

Manage different versions of datasets and finetuned models with our versioning features

More experiments is the key to success with finetuning

Experiment easily on a robust pipeline

With our hyperparameter tuning and experiment tracking features

You need Better Evaluations to build Better Solutions

Metrics for Accurate Performance Measurement

Understand strengths and weaknesses of your finetuned LLMs with our built-in metrics

Custom LLMs Without the Complexity

No-Code MLOps Pipeline for Effortless LLM Finetuning

Performance vs Cost - Based on model size

FINETUNED

GENERIC

Part of

Pipeline

Data

Finetuning

Closed and Open models

Hyperparameter Tuning

Experiment Tracking

Evaluation

Cut your costs by 200x, still get better performance!

State of the art performance at a fraction of the cost

Just an excel file is all you need

Finetune LLMs in hours, not months!

Minimal effort, maximum gains

Complete No-Code solution for finetuning LLMs

No more struggling to manage data and models

Improve your models continuously with little effort!

More experiments is the key to success with finetuning

Experiment easily on a robust pipeline

You need Better Evaluations to build Better Solutions

Metrics for Accurate Performance Measurement