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  3. jina-ai
  4. mlx-retrieval
PythonNiche visibilityStale activityNo linked package signalPartial snapshot

jina-ai/mlx-retrieval

Rank not captured·Top 100·All-time stars·◐Cached ranking snapshot·Updated Aug 15, 2026

Train embedding and reranker models for retrieval tasks on Apple Silicon with MLX

Compare closest alternativesOpen GitHub

First read

Useful directional context, not a final verdict yet

jina-ai/mlx-retrieval is better read as a directional signal than a clean recommendation. Keep the snapshot conservative and validate source activity, package reality, and close alternatives before committing to it.

Visible

187 public stars in the current GitStar snapshot.

Needs a narrower context read

Active

Last commit Sep 18, 2025.

Stale activity

Adopted

Treat stars as discovery context until a linked package appears.

No linked package mapping

Confidence

One or more key signals are partial, so GitStar keeps the interpretation conservative.

Partial snapshot

Snapshot facts

  • 187 stars
  • 12 forks
  • Last commit Sep 18, 2025
  • Package usage not mapped yet

Compare lens

huggingface/transformers and pytorch/pytorch are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.

Signal trail

Trajectory

Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.

Daily momentum
Recent momentum is not captured
Weekly momentum
Recent momentum is not captured
Monthly momentum
Recent momentum is not captured
Last commit
Sep 18, 2025

Package reality

No linked npm or PyPI package is mapped for this repository yet, so the page leans more heavily on GitHub-visible popularity and should be read more conservatively.

GitStar expects a package signal here, but no npm or PyPI package is linked to this repository yet.

Hype vs Reality
Insufficient Package Data
Package mapping
No linked package yet
Cross-links
Standalone repo read

Validation note

GitStar can summarize public signals for jina-ai/mlx-retrieval, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.

apple-siliconembeddingsmlxmtebreranker
🛡️ Editorial Context

GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.

Why this rank

This repo is here because it still carries strong GitHub attention.

📈 Momentum & Adoption Signals
Approximate star trajectory

Reconstructed from current stars and cached daily/weekly/monthly deltas.

Now: 187
30d ago7d ago1d agoNow
Daily momentum
No signal
Weekly momentum
No signal
Monthly momentum
No signal
Signal mix (log-scaled for readability)
Current stars187
🧭 Hype vs Reality
Insufficient Package Data

GitStar can see repository momentum, but it does not have a reliable linked package signal yet.

Treat stars and recent movement as discovery context only until npm or PyPI usage is available.

Status
Insufficient Package Data
Package footprint
No linked npm or PyPI usage signal
Method note
This label appears when GitStar cannot find strong enough package telemetry to compare attention against adoption. Compare it against other Python repos before treating stars as a moat.
📐 Read the Hype vs Reality heuristic
Related alternative

huggingface/transformers

Shares the ai-ml category footprint with jina-ai/mlx-retrieval, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

pytorch/pytorch

Shares the ai-ml category footprint with jina-ai/mlx-retrieval, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

d2l-ai/d2l-zh

Shares the ai-ml category footprint with jina-ai/mlx-retrieval, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Related alternative

OpenBB-finance/OpenBB

Shares the ai-ml category footprint with jina-ai/mlx-retrieval, so the comparison is closer to a same-problem decision than a same-language coincidence.

CompareOpen detail
Research links

Cross-links

Compare against related repos

GitStar picked transformers + pytorch as the closest next comparison from the related repository set.

Open compare presetCompare with transformersCompare with pytorch
Repo utility

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Wider nearby ecosystem

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《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

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labmlai/annotated_deep_learning_paper_implementations

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

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scikit-learn/scikit-learn

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Next step after the validation read

Move into a compare preset, organization view, or the heuristic notes once this first fold tells you whether the repo looks visible, active, adopted, and credible enough to keep researching.
Compare the closest alternativesView the organizationRead the heuristic

Learn and methodology

Keep trust-building context reachable, but behind the first data read instead of ahead of it.
GuideMethodologyArticlesWeekly Digest

About This Page

This page provides a quick overview of jina-ai/mlx-retrieval based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.

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