EshbanTheLearner

Eshban Suleman's starred repositories

blogs

Jupyter notebooks that support my graph data science blog posts at https://bratanic-tomaz.medium.com/

Language:Jupyter Notebook130300

LLaMA-Cult-and-More

Large Language Models for All, 🦙 Cult and More, Stay in touch !

Language:HTMLMIT42500

segmentation_models

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

Language:PythonMIT472900

awesome-computer-vision

A curated list of awesome computer vision resources

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segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Language:Jupyter NotebookApache-2.04695700

chatgpt-retrieval-plugin

The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.

Language:PythonMIT2102800

sgpt

SGPT: GPT Sentence Embeddings for Semantic Search

Language:Jupyter NotebookMIT84100

the-algorithm

Source code for Twitter's Recommendation Algorithm

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gpt4all

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

Language:C++MIT6969300

ColossalAI

Making large AI models cheaper, faster and more accessible

Language:PythonApache-2.03868800

langchain

🦜🔗 Build context-aware reasoning applications

Language:Jupyter NotebookMIT9301000

openai-cookbook

Examples and guides for using the OpenAI API

Language:MDXMIT5883000

my_notes

My small cheatsheets for data science, ML, computer science and more.

Apache-2.0162900

lazypredict

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Language:PythonMIT287000

DataScienceResources

Open Source Data Science Resources.

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cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

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Made-With-ML

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Language:Jupyter NotebookMIT3717100

linux

Linux kernel source tree

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Sphere

Web-scale retrieval for knowledge-intensive NLP

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PaLM-rlhf-pytorch

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

Language:PythonMIT767900

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

Language:Jupyter Notebook526800

annotated_deep_learning_paper_implementations

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Language:PythonMIT5444600