Skip to content

Latest commit

 

History

History
77 lines (58 loc) · 2.67 KB

ACKNOWLEDGEMENTS.md

File metadata and controls

77 lines (58 loc) · 2.67 KB

Acknowledgements and Attributions

This document acknowledges external resources, tutorials, and documentation that inspired or informed the examples in this repository.

Official MAX Documentation

MLP Example (03_mlp_regression)

The MLP implementation using max.nn.Module was inspired by the official MAX documentation:

  • Source: Build an MLP block as a module
  • Concepts adapted:
    • Using Module class for layer composition
    • __call__ method for forward pass
    • Layer stacking with ReLU activations
  • Our additions:
    • Applied to regression task (California housing dataset)
    • Pre-trained weights included
    • Complete end-to-end inference example
    • Benchmarking against PyTorch

MAX Graph API Fundamentals

General MAX Graph concepts learned from:

Datasets

California Housing

  • Source: scikit-learn's fetch_california_housing()
  • Usage: MLP regression example
  • License: BSD-3-Clause (scikit-learn)

MNIST

  • Source: torchvision's MNIST dataset
  • Usage: CNN classifier example
  • License: Creative Commons Attribution-Share Alike 3.0

Models

DistilBERT

  • Source: Hugging Face model hub
  • Model: distilbert-base-uncased-finetuned-sst-2-english
  • Original paper: "DistilBERT, a distilled version of BERT" (Sanh et al., 2019)
  • License: Apache 2.0

Community Contributions

This repository has been improved through:

  • Feedback from the Modular Discord community
  • Early testing and bug reports from users
  • Suggestions for additional examples and clarifications

Tools and Frameworks

  • MAX Engine: Modular's high-performance inference framework
  • Pixi: Package manager for managing dependencies
  • PyTorch: Used for benchmarking comparisons and dataset loading
  • Hugging Face Transformers: Model and tokeniser loading

Learning Resources

Key resources that informed our understanding:

  • Modular's official documentation and tutorials
  • MAX GitHub repository examples
  • Community discussions on Modular forums and Discord

How to Contribute Attributions

If you notice missing attributions or have suggestions for acknowledgements:

  1. Open an issue on GitHub
  2. Provide the source/resource details
  3. Describe how it relates to our examples

We strive to properly acknowledge all inspirations and sources.