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Levanter

Fine-Tuning 3.9/10 Emerging

Legible, Scalable, Reproducible Foundation Models with Named Tensors and Jax

Levanter scores 3.9/10 (Emerging) in Fine-Tuning.

Language Python License Apache-2.0 Stars 706★ Type library Self-host Yes Repo stanford-crfm/levanter Homepage https://github.com/stanford-crfm/levanter

Quality

Emerging 3.9
Adoption 21
Activity 11
Maturity 92
Community 28
Capability 50
Show the math
Overall 3.9/10
value = 3.9/10
score = value
Adoption 2.9/10
value = 21.2/100
score = 1 + 9 * value / 100
Activity 2/10
value = 11/100
score = 1 + 9 * value / 100
Maturity 9.3/10
value = 91.8/100
score = 1 + 9 * value / 100
Community 3.5/10
value = 28.2/100
score = 1 + 9 * value / 100
Capability 5.5/10
value = 50/100
score = 1 + 9 * value / 100

Key metrics

706★ GitHub stars
0/90d Recent commits
0 devs/90d Recent contributors
4.1y Project age
5mo ago Last commit

Gotchas

No gotchas documented yet. Contribute one if you know a constraint we missed.

Labels

  • Self-hosted

    Self-hosted

    You deploy and operate it yourself; there is no hosted option here.

jax tpu training reproducible scalable