README.md

metadata

pretty_name: Embedding Quantization Reproducibility Bundle
license: apache-2.0
tags:
  - embeddings
  - quantization
  - mlx
  - zerogpu
  - reproducibility

Embedding quantization reproducibility bundle

This dataset contains the frozen inputs, vector artifacts, metrics, calibration evidence, and scripts behind the companion engineering post on MLX Q/oQ/oQe embedding quantization and CUDA-native controls.

See RESULTS.md for the compact result tables and evidence boundaries.

The model weights are not duplicated here. models.lock.json pins all 30 public model repositories to exact Hub commits and records their canonical upstream BF16 revisions. Quantized artifacts branch directly from their family's BF16 checkpoint; no lossy conversion was used as another quantization's source.

Verify the published evidence

hf download TiGa-RCE/embedding-quant-repro-2026-07-28 \
  --repo-type dataset --local-dir embedding-quant-repro
cd embedding-quant-repro
uv sync
uv run python reproduce.py verify
uv run python reproduce.py mixed-index

verify checks the locked revisions, bundle checksums, all 30 saved MLX vector artifacts, and the three-family mixed-index result. mixed-index regenerates the 54 migration-direction measurements from the saved vectors without downloading model weights.

Local MLX gate on Apple Silicon

The quick profile downloads the locked 0.6B BF16 and representative Q4/Q6/Q8 artifacts, then reproduces their vector comparisons:

uv sync --extra mlx
uv run python reproduce.py mlx --profile quick

The complete matrix is intentionally explicit because it downloads all 30 checkpoints:

uv run python reproduce.py mlx --profile full --family all

CUDA controls through ZeroGPU

After authenticating with Hugging Face, the client invokes the bounded BF16, bitsandbytes INT8, and bitsandbytes NF4 controls:

hf auth login
uv sync --extra zerogpu
uv run python reproduce.py cuda

These bitsandbytes results are controls, not MLX Q/oQ/oQe equivalents. ZeroGPU quota and scheduling still apply. The default runs the three 0.6B controls. The complete nine-run matrix is deliberately explicit because it can exceed a free account's daily quota:

uv run python reproduce.py cuda --family all --variant all

Evidence boundaries

• The frozen set has 24 query/document pairs. This is an engineering smoke test, not MTEB or a universal retrieval-quality claim.
• Q4 remains in the bundle as an intentionally failed fidelity comparator.
• GTE-Qwen2 1.5B CUDA vectors are quarantined from MLX cross-runtime trends because that family failed loading-path parity.
• scripts/frozen-original/ preserves the exact experiment scripts, including their historical local paths. Use reproduce.py for the portable interface.
• The bundle contains no credentials.