Catalog Systems Training infrastructure Composer (MosaicML)

Composer (MosaicML)

https://github.com/mosaicml/composer

Open-source training library from MosaicML (Databricks) — Trainer + recipes for fast convergence; underlies the MPT model training stack.

Archived. repository archived (read-only) Source

Archived · Verified 2026-10-27 · fresh as of 2026-10-27 · 18 cited facts, 2 with a third-party source · 1 recorded change · Suggest a correction

At a glance

Type
PyTorch training library repo fix
Tier
T2
Section
Training infrastructure
Created
2022 repo fix
Latest release
v0.32.1 (2025-07-26) — mosaicml registry fix
License
Apache-2.0 repo fix
GitHub
mosaicml/composer — ~5.5k stars, archived 2026-10-23, last push 2026-04 repo fix
Pricing
searched not found fix
Funding
MosaicML acquired by Databricks for $1.3B in 2023-07; Composer remains Apache-2 OSS. third-party fix
Freshness
2026-10-27 fix
Layer
model-infra repo fix
Licensing
open-source repo fix
Deployment locus
local repo fix
Platform vs product
platform repo fix
Developer activity
OpenRank 0.17 (12-mo avg 7.44) · 2 participants — 2026-09 third-party fix

When to use

Optimised for: searched not found

Anti-fit: searched not found

Pros & cons

Pros

searched not found

Cons

searched not found

Claims & capabilities

MosaicML acquired by Databricks $1.3B (2023).

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
Self-hosted only — library
Embedding model
not applicable — not a memory product
Multi-tenancy
searched not found
MCP
searched not found
A2A
searched not found
OpenTelemetry
searched not found

Similar systems

Other training infrastructure in the catalog, ranked by inbound references.

  • MLflow T1

    Databricks-incubated open platform for ML lifecycle — tracking, projects, models, model registry. Standard ML-ops baseline. MLflow 3.0 (2024) added LLM-eval features.

  • AWS SageMaker T1

    AWS's managed ML platform — Studio, Training, HyperPod (large-scale clusters), Endpoints. Industry-standard for enterprise AWS-hosted training.

  • Weights & Biases T1

    Experiment-tracking and ML-ops platform (metrics, artifacts, sweeps, Weave tracing/evals). Acquired by CoreWeave (completed 2025-05-05, ~$1.7B); now part of CoreWeave Forge.

  • Comet ML T2

    ML experiment tracking + LLM evaluation platform (Opik for LLM eval). Comet competes head-to-head with Weights & Biases.

  • Azure Machine Learning T1

    Microsoft Azure's managed ML platform — pipelines, AutoML, Designer, prompt flow (LLM). Heavy integration with Azure OpenAI and Azure AI Studio.

  • LoRA T3

    Microsoft Research's Low-Rank Adapters method — trains rank-r matrices added to attention weights; 10000x parameter reduction. Foundation of all adapter-style fine-tuning.

Sources (17 cited facts, 2 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-27
    • Lifecycle first recorded as “archived”
    • Latest release first recorded as “v0.32.1 (2025-07-26) — mosaicml” source
    • Deployment first recorded as “Self-hosted only — library” source
    #271