Environments
Get Environments
Get Environments
GET
Authorizations
Response
200 - application/json
Get Environments
Example:
[
{
"description": "Python environment for working with AI tools and SDKs. Includes tools like AlphAI, OpenAI/Anthropic/Cohere SDKs, Scikit Learn, pandas, and numpy.",
"environment_id": "ai",
"name": "AI"
},
{
"description": "Environment equipped with PyTorch, a powerful open-source tensor library for training neural network models written for Python.",
"environment_id": "torch",
"name": "PyTorch"
},
{
"description": "Environment set up for JAX, a library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning.",
"environment_id": "jax",
"name": "JAX"
},
{
"description": "Python environment for working with Hugging Face tools like transformers and datasets. Contains the Hugging Face Notebooks repostory and is powered by PyTorch.",
"environment_id": "huggingface",
"name": "Hugging Face"
},
{
"description": "Python environment for working with RAPIDS.ai tools like cuDF, cuML, cuGraph, etc. all powered by NVIDIA GPUs.",
"environment_id": "rapidsai",
"name": "RAPIDS.ai"
},
{
"description": "Environment set up for CuPy, a GPU-accelerated library for numerical computations; NumPy and SciPy for GPUs.",
"environment_id": "cupy",
"name": "CuPy"
},
{
"description": "Environment equipped with Numba, a just-in-time compiler for Python that helps developers acclerate scientific computing with GPUs.",
"environment_id": "numba",
"name": "Numba"
},
{
"description": "Environment for AI in chemistry and material science @ Meta. Previously known as Open Catalyst Project.",
"environment_id": "fairchem",
"name": "FAIR Chemistry"
},
{
"description": "Environment for PyTorch Geometric, a Graph Neural Network Library for PyTorch",
"environment_id": "pyg",
"name": "PyTorch Geometric"
}
]
Example:
"success"