πŸ› οΈ
Awesome Pytorch List tool by bharathgs
⭐ 47.9
πŸ› οΈ
Tool

Awesome Pytorch List

by bharathgs bharathgs/awesome-pytorch-list
Free2AITools Nexus Index
47.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 61
P: Popularity 72
R: Recency 72
Q: Quality 70
Tech Context
Vital Performance —
Source β†’
- Lang
16.6K Stars
Alpha Reliability
Tool Information Summary
Entity Passport
Registry ID bharathgs/awesome-pytorch-list
Provider github
πŸ“œ

Cite this tool

Academic & Research Attribution

BibTeX 
@misc{gh_tool_bharathgs_awesome_pytorch_list,
  author = {bharathgs},
  title = {Awesome Pytorch List Tool},
  year = {2026},
  howpublished = {\url{https://github.com/bharathgs/Awesome-pytorch-list}},
  note = {Accessed via Free2AITools.}
}
APA Style
bharathgs. (2026). Awesome Pytorch List [Tool]. Free2AITools. https://github.com/bharathgs/Awesome-pytorch-list

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ™ GitHub Clone
git clone https://github.com/bharathgs/Awesome-pytorch-list
πŸ™ Git Clone
git clone https://github.com/bharathgs/Awesome-pytorch-list

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 61
Popularity (P) 72
Recency (R) 72
Quality (Q) 70

πŸ’¬ Index Insight

FNI V2.0 for Awesome Pytorch List: Authority (A:61), Popularity (P:72), Recency (R:72), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data

πŸ“‹ Specs

Language
β€”
License
β€”
Version
β€”
Explore Source Node

Technical Documentation

Awesome-Pytorch-list

pytorch-logo-dark

Contents

  1. pytorch: Tensors and Dynamic neural networks in Python with strong GPU acceleration.
  2. Captum: Model interpretability and understanding for PyTorch.

NLP & Speech Processing:

  1. pytorch text: Torch text related contents.
  2. pytorch-seq2seq: A framework for sequence-to-sequence (seq2seq) models implemented in PyTorch.
  3. anuvada: Interpretable Models for NLP using PyTorch.
  4. audio: simple audio I/O for pytorch.
  5. loop: A method to generate speech across multiple speakers
  6. fairseq-py: Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
  7. speech: PyTorch ASR Implementation.
  8. OpenNMT-py: Open-Source Neural Machine Translation in PyTorch http://opennmt.net
  9. neuralcoref: State-of-the-art coreference reso

Social Proof

GitHub Repository
16.6KStars
2.8KForks
Repo Issues
πŸ™ Data Source: GitHub β†—
πŸ”„ Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Tool Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
gh-tool--bharathgs--awesome-pytorch-list
slug
bharathgs--awesome-pytorch-list
source
github
author
bharathgs
license
tags
pytorch, python, machine-learning, deep-learning, tutorials, papers, awesome, awesome-list, pytorch-tutorials, data-science, nlp, nlp-library, cv, computer-vision, natural-language-processing, facebook, probabilistic-programming, utility-library, neural-network, pytorch-model

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
other

πŸ“Š Engagement & Metrics

downloads
0
stars
16,571
forks
2,836
github stars
16,571

Data indexed from public sources. Updated daily.