Fine-tuned on AMD MI300X for the AMD Developer Hackathon 2026 (Fine-Tuning Track).
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A simple guide to fine-tuning Llama 2 Brev docs provides machine-learning models, research, training resources, or evaluation tools.
Documentation for Fine Tuning Guide, covering setup, features, and practical usage.
USE BAZEL VERSION=5.0.0./bazelisk-linux-amd64 build wavegru mod -c opt --copt=-march=native.
Open-source implementation of Google Vizier for hyper parameters tuning.
Tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures.
Scalable deep learning training platform with integrated hyperparameter tuning support; includes Hyperband, PBT, and other search methods.
PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
Open source, high performance fine tuning as a service for GPT4 quality models with 5x lower latency and 3x lower cost.
Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.
Kubernetes-based system for hyperparameter tuning and neural architecture search.
Build better AI systems with evals, RAG, agents, synthetic data, fine-tuning, and prompt optimization. Free app + open-source library.
No-code batch compute platform for LLM evaluation and tuning workloads.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
State-of-the-art Parameter-Efficient Fine-Tuning.
An MLOps/LLMOps platform for model building, evaluation, and fine-tuning.
Build and control your personal LLMs with fast and efficient fine-tuning.
Lightweight ML utility for automated training, evaluation, and prediction with CLI and Python API support.
A CLI utility to train and deploy ML/DL models on AWS SageMaker.