ustcllm/RecFM

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1033 stars · 667 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

RecFM is a collection of tools and frameworks from USTCLLM for developing foundation models tailored to recommendation systems. It bundles modular training libraries (RecStudio, RecStudio4Industry, Nexus) and text embedding alignment models (CELA, GRE) for building and deploying recommender models.

Use cases

• build and train recommendation system models in PyTorch
• deploy multi-stage recommendation services in industry settings
• convert text embedding models for recommendation use
• extract universal text representations for multi-domain recommendation
• build document retrieval and information retrieval pipelines
• visualize and debug recommendation model training

When to choose

• you need a modular library for rapid recommender model prototyping and training
• you want industrial-scale recommendation training with HDFS-friendly data interfaces
• you need text embeddings aligned for recommendation tasks
• you are building multi-stage recommendation or retrieval services

When to avoid

• you need a turnkey hosted recommendation service rather than a toolkit
• your project is unrelated to recommendation or retrieval
• you require a single unified package rather than multiple subprojects

Facets

framework · maturity active

machine-learning deep-learning search-engine data-science sdk machine-learning large-language-models data-science python recommendation-systems foundation-models retrieval text-embedding recsys retrieval-augmented-generation search

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markdown · JSON · MCP: product_card(name="ustcllm/RecFM")