ndif-team/nnsight
The nnsight package enables interpreting and manipulating the internals of deep learned models.
This tool helps AI researchers and machine learning engineers understand and modify how deep learning models, especially large language models, process information. You input a pre-trained PyTorch model and text prompts, and it allows you to observe or change the internal computations (activations) at any layer. The output provides insights into the model's internal workings or modified model behavior.
859 stars. Used by 1 other package. Actively maintained with 20 commits in the last 30 days. Available on PyPI.
Use this if you need to meticulously examine, debug, or causally intervene on the internal computations of a deep learning model to understand its decision-making process.
Not ideal if you are looking for a high-level API for model training, deployment, or general inference without needing deep internal inspection or manipulation.
Stars
859
Forks
79
Language
Python
License
MIT
Category
Last pushed
Mar 13, 2026
Commits (30d)
20
Dependencies
12
Reverse dependents
1
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ndif-team/nnsight"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
huggingface/dataset-viewer
Backend that powers the dataset viewer on Hugging Face dataset pages through a public API.
LYH-YF/MWPToolkit
MWPToolkit is an open-source framework for math word problem(MWP) solvers.
epfml/disco
DISCO is a code-free and installation-free browser platform that allows any non-technical user...
ndif-team/ndif
The NDIF server, which performs deep inference and serves nnsight requests remotely
WarBean/hyperboard
A web-based dashboard for Deep Learning