What is Autolabel?
It is a Python library to label, clean, and enrich text datasets with any Large Language Models (LLMs) of your choice.
Autolabel is a tool in the Datasets & Benchmarks category of a tech stack.
Key Features
Autolabel data for NLP tasks such as classification, entity matching, and moreSeamlessly use commercial and open source LLMs from providers such as OpenAI, HuggingFace, Google, and moreLeverage research-proven LLM techniques to boost label qualityCaching and state management to minimize costs and experimentation time
Autolabel Pros & Cons
Pros of Autolabel
No pros listed yet.
Cons of Autolabel
No cons listed yet.
Autolabel Alternatives & Comparisons
What are some alternatives to Autolabel?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
