knum-mimuw / podstawy-dl-2019Links
Materiały z warsztatów z podstaw Deep Learningu dla początkujących. Wiosna 2019.
☆13Updated 6 years ago
Alternatives and similar repositories for podstawy-dl-2019
Users that are interested in podstawy-dl-2019 are comparing it to the libraries listed below
Sorting:
- A platform for managing machine learning experiments☆885Updated 2 months ago
- Puzzles for exploring transformers☆380Updated 2 years ago
- Version control for machine learning☆1,671Updated 9 months ago
- Task-based datasets, preprocessing, and evaluation for sequence models.☆591Updated last month
- tree is a library for working with nested data structures☆1,013Updated 10 months ago
- See the issue board for the current status of active and prospective projects!☆65Updated 3 years ago
- Helps you write algorithms in PyTorch that adapt to the available (CUDA) memory☆438Updated last year
- The simplest machine learning library for launching UIs, running evaluations, and comparing model performance.☆13Updated 2 years ago
- ☆283Updated last year
- A library for bridging Python and HTML/Javascript (via Svelte) for creating interactive visualizations☆201Updated 3 years ago
- A prize for finding tasks that cause large language models to show inverse scaling☆619Updated 2 years ago
- Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.☆1,466Updated 7 months ago
- A walkthrough of transformer architecture code☆371Updated last year
- ☆56Updated 2 months ago
- Solve puzzles. Learn CUDA.☆64Updated 2 years ago
- Named tensors with first-class dimensions for PyTorch☆332Updated 2 years ago
- ☆14Updated 3 years ago
- Highly commented implementations of Transformers in PyTorch☆139Updated 2 years ago
- ☆549Updated last year
- ☆460Updated last year
- An implementation of masked language modeling for Pytorch, made as concise and simple as possible☆179Updated 2 years ago
- Manage ML configuration with pydantic☆16Updated 6 months ago
- A library that integrates huggingface transformers with the world of fastai, giving fastai devs everything they need to train, evaluate, …☆297Updated last year
- Swarm training framework using Haiku + JAX + Ray for layer parallel transformer language models on unreliable, heterogeneous nodes☆242Updated 2 years ago
- An interactive exploration of Transformer programming.☆270Updated 2 years ago
- 100 exercises to learn JAX☆594Updated 3 years ago
- 🧠 Starter templates for doing interpretability research☆74Updated 2 years ago
- Mechanistic Interpretability Visualizations using React☆304Updated last year
- Memory mapped numpy arrays of varying shapes☆307Updated last year
- Machine Learning for Alignment Bootcamp☆81Updated 3 years ago