Bump nnsight from 0.5.13 to 0.6.1

[dependabot]

Bumps nnsight from 0.5.13 to 0.6.1.

Release notes

Sourced from nnsight's releases.

v0.6.1

Bug fix for workbench on 0.6 release.

Full Changelog: ndif-team/nnsight@v0.6.0...v0.6.1

v0.6.0

nnsight v0.6.0 Release Notes

🚀 Highlights

Seamless Custom Code on NDIF

The biggest change in this release is a new serialization format that enables your local packages to work seamlessly on NDIF—even if they aren't installed on the server.

How it works: nnsight now serializes functions and classes by value (source code) rather than by reference. This means your local packages are sent along with your request and rebuilt on the server—even if they aren't installed on NDIF.

from nnsight import ndif, LanguageModel
import mymodule
Register your module for remote execution
ndif.register(mymodule)
model = LanguageModel("meta-llama/Llama-3.1-70B")
with model.trace("Hello world", remote=True):
result = mymodule.my_analysis_function(model).save()

What gets auto-registered: Code you write yourself is sent automatically—you don't need to do anything. Specifically:

• Your script and its local imports. Any code defined in the file you're running, plus any .py files it imports from the same directory or project, are sent with the request.
• Editable/dev-installed packages. If you ran pip install -e . on a package, nnsight detects it isn't a regular site-package and sends it too.

What needs ndif.register(): Packages installed normally via pip install (i.e. living in site-packages) are assumed to already exist on the server and are not sent. If you have a pip-installed package that NDIF doesn't have, call ndif.register(pkg) to explicitly include it.

Python version flexibility: The new serialization format enables Python 3.9+ clients to work with NDIF regardless of the server's Python version.

A real example of where this matters: nnterp is a library built on nnsight that standardizes transformer interfaces across model families. NDIF doesn't have nnterp installed, but that doesn't matter—just register it:

from nnterp import StandardizedTransformer
from nnsight import ndif
import nnterp
ndif.register(nnterp)
model = StandardizedTransformer("meta-llama/Llama-3.1-70B")
with model.trace("hello", remote=True):
</tr></table>

... (truncated)

Commits

• 3fd13f8 Only get source code via '-c' argv if getting from a regular file fails first
• 9340e12 remove links to images
• 16dbb68 Merge pull request #618 from ndif-team/v0.5.16
• 2b15e19 add doc
• b4e920f Merge pull request #617 from ndif-team/dev
• 9853301 Merge pull request #594 from ndif-team/v0.5.16
• 053a885 improve 0.6 notes
• 16c4e2c Move vLLM section before for-loop iteration in release notes
• 25a1757 Update release notes: add async vLLM, reorder highlights, expand NDIF utilities
• 6365233 Merge branch 'v0.5.16' of github.com:ndif-team/nnsight into v0.5.16
• Additional commits viewable in compare view

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Project	Deployment	Actions	Updated (UTC)
workbench	Ready	Preview, Comment	Mar 2, 2026 5:12pm

[dependabot]

Superseded by #107.