bytedance/monolith

Health v2 · maintenance only

Flags: no_releases archived no_license

Adoption not part of the score

9298 stars · 719 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Monolith is a deep learning framework built on TensorFlow for large-scale recommendation modeling. It provides collisionless embedding tables for unique id feature representations and supports real-time training to capture emerging user interests.

Use cases

• build large-scale recommendation systems
• train models with collisionless embedding tables
• run real-time training for recommendation models
• serve recommendation models in production
• distributed async training of deep learning models

When to choose

• you need a specialized framework for large-scale recommendation modeling
• you want collisionless embedding tables for id features
• you need real-time training to capture latest user interests
• you are building on TensorFlow infrastructure

When to avoid

• you need a general-purpose deep learning framework outside recommendations
• you require compilation on platforms other than Linux
• you want a lightweight solution without Bazel build complexity

Facets

framework · maturity active

deep-learning machine-learning llm-training machine-learning deep-learning python recommendation-system tensorflow embedding-tables real-time-training collaborative-filtering distributed-training recommendation-systems linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="bytedance/monolith")