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trueno-quant

v0.1.0 Experimental

K-quantization formats (Q4_K, Q5_K, Q6_K) for GGUF/APR model weights

MIT OR Apache-2.0 Edition 2021
AlgorithmsCompressionScience #quantization#neural-network#machine-learning#llm#gguf

Quick Verdict

  • โœ“Actively maintained (updated 44d ago)
  • !Pre-1.0: API may have breaking changes
  • โœ“Tiny footprint (8KB, 1 deps)
  • โœ“Permissive license (MIT OR Apache-2.0)

Security

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Downloads
8.6K
Dependents
31
Releases
1
Size
8KB

Deep Insights

๐Ÿ“ˆ
Strong growth momentum

6.7K downloads in the last 30 days (225/day), up 243% from the previous period.

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Prolific maintainer

The primary maintainer publishes 160 crates. This suggests deep Rust expertise and long-term commitment to the ecosystem.

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Minimal dependencies

Only 1 direct dependencies. Lean dependency tree means faster builds and lower supply chain risk.

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Compact crate

At 8KB, trueno-quant is lightweight. Small crate size correlates with focused, well-scoped functionality.

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Used by top crates

Notable dependents include trueno, aprender, realizar. When high-quality crates choose trueno-quant, it's a strong quality signal.

Health Breakdown

Maintenance 10/25

Recency, release consistency, active ratio

Quality 14/25

Yanked ratio, deps, size, maturity, features

Community 10/20

Reverse deps, ownership, ecosystem

Popularity 5/15

Downloads, momentum, growth trend

Documentation 10/15

Docs, repo, license, metadata

Download Trend

Daily downloads ยท last 90 days
97/day avg
010020030040050012/291/162/32/213/113/28

Top Dependents

Most downloaded crates that depend on trueno-quant

Version Adoption

v0.1.0
100%

Release Timeline

1 releasessince 2026
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README

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Maintainers

Dependencies
1
direct dependencies
Dependents
31
crates depend on trueno-quant

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