Leeroo Client
Leeroo Dager offers a comprehensive solution for developing custom AI models. By simply defining your evaluation system, and providing seed data, Leeroo automates the entire workflow from data generation to model training and evaluation. No AI expertise is required—Leeroo ensures the delivery of the best customized model tailored to your specifications. Model deployment is streamlined and can be achieved with a single command.
Installation
Install using pip
pip install leeroo-client
Install from Source
git clone https://github.com/Leeroo-AI/leeroo-client
cd leeroo-client
pip install -e .
Features
Synthetic Data Generation
Our advanced data generation pipeline employs multi-agent systems to create diverse training data, ensuring enhanced generalization and reliability.
Training
Our training pipeline is designed to execute optimal experiments tailored to your use case on any cloud provider. By integrating state-of-the-art techniques such as SFT, DPO, RLHF or building compound models, we consistently deliver high-performing custom models.
Evaluation
Utilize our Multi-Model LLM System to create high-quality LLM as judge Evaluation systems.
Deployment
Automatically deploy customized AI models without the need for AI Infra expertise. Uses VLLM / Fastchat for deployment.
Metadata
Release files for leeroo-client 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| leeroo_client-0.0.2.tar.gz | 13.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| leeroo_client-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 26.5 kB
Release files / leeroo_client-0.0.2.tar.gz
| Download URL | leeroo_client-0.0.2.tar.gz |
|---|---|
| Size | 13.8 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.14
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Release files / leeroo_client-0.0.2-py3-none-any.whl
| Download URL | leeroo_client-0.0.2-py3-none-any.whl |
|---|---|
| Size | 12.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.14
|