Skip to main content

NAM: Neural Amp Modeler

Build

This repository handles training models and exporting them to .nam files. For playing trained models in real time in a standalone application or plugin, see the partner repo, NeuralAmpModelerPlugin.

For more information about the NAM ecosystem please check out https://www.neuralampmodeler.com/.

Documentation

Online documentation can be found here: https://neural-amp-modeler.readthedocs.io

To build the documentation locally on a Linux system:

cd docs
make html

Or on Windows,

cd docs
make.bat html

Metadata

Release files for neural-amp-modeler 0.13.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for neural-amp-modeler 0.13.0
File Size Uploaded Provenance Actions
neural_amp_modeler-0.13.0.tar.gz 20.4 MB Without provenance Details for neural_amp_modeler-0.13.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for neural-amp-modeler 0.13.0
File Interpreter ABI Platform Actions
neural_amp_modeler-0.13.0-py3-none-any.whl Python 3 none any Details for neural_amp_modeler-0.13.0-py3-none-any.whl

Total release size: 20.7 MB

Release files / neural_amp_modeler-0.13.0.tar.gz

Download URL neural_amp_modeler-0.13.0.tar.gz
Size 20.4 MB
Tags Source
SHA-256 checksum
How to use checksums
550710fc50aa374178bc739c0e55141b6c17e2749aad17b74fab02069484b8e4
BLAKE2b-256 checksum
How to use checksums
58ce47ad40574ac9db26e19e67f4bc956045c709f4c545649bf9bbf3c52857e7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.2

Release files / neural_amp_modeler-0.13.0-py3-none-any.whl

Download URL neural_amp_modeler-0.13.0-py3-none-any.whl
Size 271.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
403531a815f23d2628c7afcf85c18a522db57838c36af44cf8b1e1048cc53129
BLAKE2b-256 checksum
How to use checksums
f3f90d07b9cb2afe88cf621753a27000dbd8f249bfc8fa3263531d0f29c32e98
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.2

Security for neural-amp-modeler 0.13.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page