# higgsfield-ai/higgsfield

> Fault-tolerant GPU orchestration and ML framework for distributed training of models with billions to trillions of parameters, including LLMs. Manages node access, experiment queueing, and GitHub Actions integration.

- Magnitude: 1.4 out of 10 — Cooling
- Stars: 5,832 total · +3 stars on 2026-10-01 (UTC), ≈ 9 by evening
- Star trust: star growth looks organic
- Category: Language models · Language: Jupyter Notebook · License: Apache-2.0 · Created: 2018-05-26 · Last push: 2026-09-14
- GitHub: https://github.com/higgsfield-ai/higgsfield · Page: https://gitnova.dev/en/r/higgsfield-ai/higgsfield

## Useful for

- Run distributed LLaMa 70B training across multiple GPU nodes using ZeRO-3
- Set up an experiment queue to manage contention for compute resources
- Integrate model training with GitHub Actions for ML CI/CD pipelines

## Why it’s here

- 3 stars so far today, about 9 expected by the end of the day.
- Interest is fading: the two-day pace is 9% of the previous week and a half.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 1,043
- Issues and pull requests: 32
- Watchers: 90
- Average over the last week: 20 per day
- Usual pace: 100 per day
- Latest release: v0.0.4-rc (2024-03-23)

## Stars per day, last 30 days (oldest → newest, today is partial)

2026-10-05 … 2026-11-03: None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None

## Magnitude by day, last 13 days

09-19 6.7, 09-20 7.2, 09-21 6.9, 09-22 4.8, 09-23 3.3, 09-24 2.8, 09-25 2.4, 09-26 2.2, 09-27 1.8, 09-28 1.8, 09-29 1.7, 09-30 1.4, 10-01 1.4

---

Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-10-01 11:14 UTC, updated every 30 minutes.