semvec/pypi-packages huggingface dataset:
multi-model-trainers 0.0.1
Multi-Model-Trainer - Pytorch
License: MIT
Requires Python: <4.0,>=3.10
Keywords: artificial intelligence, deep learning, optimizers, Prompt Engineering

[![Multi-Modality](agorabanner.png)](https://discord.com/servers/agora-999382051935506503)

# Multi-Model Trainers

## Install

## Usage


# License
MIT
fastwonn 0.0.9
Fast, GPU-friendly, differentiable computation of Intrinsic Dimension via Maximum Likelihood, the TwoNN algorithm, and everything in between!
License: MIT
Requires Python: >=3.10
Keywords: Deep Learning, Differentiable Programming, Intrinsic Dimension, Machine Learning, Manifold Learning, Maximum Likelihood Estimation, PyTorch, TwoNN

# `fastwonn`

Fast, GPU-friendly, differentiable computation of Intrinsic Dimension via Maximum Likelihood (Levina & Bickel, 2004), the TwoNN algorithm (Facco et al., 2017), and everything in between!

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### References
- [E. Levina, P. Bickel; "Maximum Likelihood Estimation of Intrinsic Dimension", Advances in Neural Information Processing Systems, 2004](https://papers.nips.cc/paper_files/paper/2004/hash/74934548253bcab8490ebd74afed7031-Abstract.html)
- [E. Facco, M. d'Errico, A. Rodriguez, A. Laio; "Estimating the intrinsic dimension of datasets by a minimal neighborhood information", Nature Scientific Reports, 2017](https://www.nature.com/articles/s41598-017-11873-y)