Exorust/TorchLeet resource
LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor. observed · 2026-08-28
Health v2 · maintenance only
65/100
- Activity 98
- Release rhythm 35
- Longevity 44
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 617
- days_rel: n/a
- days_push: 14
- n_releases_24m: 0
Adoption not part of the score
2430 stars · 305 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
TorchLeet is a collection of 65 PyTorch practice problems drawn from real ML/AI interviews at companies like Google, Meta, and Anthropic, delivered as Jupyter notebooks with an auto-grader. It includes an MCP server that turns AI assistants into a no-spoilers PyTorch interview tutor with hints, mock interviews, and learning paths.
Use cases
- prepare for ML/AI coding interviews with PyTorch problems
- practice implementing transformers, attention, and RLHF from scratch
- build an LLM from scratch as a guided learning path
- get AI-tutored PyTorch practice with progressive hints via MCP
- practice problems asked at Google, Meta, Anthropic, and OpenAI interviews
- check my PyTorch solutions automatically with an auto-grader
When to choose
- you are preparing for machine learning or AI engineer interviews and want hands-on PyTorch practice
- you want to deeply understand PyTorch internals by implementing things from scratch without LLM help
- you want a structured curriculum covering basics through advanced topics like Triton kernels, KV cache, and DPO
- you want an AI tutor that guides without spoiling solutions
When to avoid
- you need a production ML library or framework rather than practice exercises
- you are a complete beginner to Python or deep learning with no PyTorch basics
- you want quick answers generated by an LLM rather than struggling through problems yourself
Facets
learning-resource · maturity active
machine-learning deep-learning llm-training prompt-engineering mcp testing machine-learning deep-learning large-language-models education tutorials python cross-platform pytorch interview-preparation leetcode jupyter-notebooks auto-grader rlhf transformers triton coding-interviews mcp-server web
3 sources
- readme: https://github.com/Exorust/TorchLeet · fetched 2026-08-28 · 4936761a5a92
- homepage: https://torch-leet.vercel.app · fetched 2026-08-29 · 4034b4ba8513
- registry_pypi: https://pypi.org/pypi/torchleet/json · fetched 2026-08-29 · c2744b0acd4a
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Exorust/TorchLeet | main | 65 |
For agents
markdown · JSON · MCP: product_card(name="Exorust/TorchLeet")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem