Feature Extraction
MLX
Safetensors
qwen3
apple-silicon
quantized
mixed-precision
axquant
axq
development
MXFP8
embedding
sentence-similarity
8-bit precision
Instructions to use AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP8 --local-dir AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Correct evidenced MXFP8 container mode and bind runtime format audit
Browse files- README.md +13 -0
- axquant_manifest.json +10 -5
- config.json +0 -0
- runtime_audit.json +62 -0
README.md
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@@ -19,6 +19,19 @@ tags:
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- sentence-similarity
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---
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# AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP8 — 8.25 BPW measured main
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An **AXQuant (AXQ)** mixed-precision MLX checkpoint for Apple Silicon, converted directly from
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- sentence-similarity
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---
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## Runtime format audit (2026-10-06)
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The quantization container mode was corrected from `affine` to `mxfp8`
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in both config blocks after inspecting every quantized module header.
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Weight bytes and per-module precision assignments are unchanged.
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This family has no n-gram tensors; no n-gram file or declaration was added.
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This remote format audit does not grant an oMLX/MTPLX runtime profile or a successful load/generation claim.
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See [runtime_audit.json](runtime_audit.json) for pinned config/index/header
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bindings, architecture, physical-format findings, and applied corrections.
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This is development evidence; no quality, MTP exactness, speed, or certification
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claim is added. Historical evidence stays bound to its original revision.
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# AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP8 — 8.25 BPW measured main
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An **AXQuant (AXQ)** mixed-precision MLX checkpoint for Apple Silicon, converted directly from
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axquant_manifest.json
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{
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"axquant_version": "1.9.0",
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"calibration": null,
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-
"created_at": "2026-10-
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"effective_bpw": 9.000770006857874,
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"files": [
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{
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},
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{
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"path": "README.md",
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"sha256": "
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"size_bytes":
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},
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{
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"path": "axquant_plan.json",
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},
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{
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"path": "config.json",
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"sha256": "
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"size_bytes":
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},
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{
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"path": "config_sentence_transformers.json",
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"sha256": "84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf",
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"size_bytes": 349
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},
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{
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"path": "tokenizer.json",
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"sha256": "93623af029cdc69b87f2864d3b2cc2424fdf16684f15e139b5b9d08ec34ced91",
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{
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"axquant_version": "1.9.0",
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"calibration": null,
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"created_at": "2026-10-06T21:01:14.077738+00:00",
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"effective_bpw": 9.000770006857874,
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"files": [
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{
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},
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{
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"path": "README.md",
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"sha256": "77b189e19bdfa84fd8e9df7172bb7e0b371991f7cf85c20b35752f21a27800e6",
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"size_bytes": 8506
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},
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{
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"path": "axquant_plan.json",
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},
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{
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"path": "config.json",
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"sha256": "b49450c5c373f46fa637822bbbd466ada245fb3b58c40e589d41a8932070670f",
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"size_bytes": 44242
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},
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{
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"path": "config_sentence_transformers.json",
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"sha256": "84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf",
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"size_bytes": 349
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},
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{
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"path": "runtime_audit.json",
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"sha256": "abf8214273c17b842205bad9015e23388a2b81aa8c44b08506c562e57f9babf0",
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"size_bytes": 2016
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},
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{
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"path": "tokenizer.json",
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"sha256": "93623af029cdc69b87f2864d3b2cc2424fdf16684f15e139b5b9d08ec34ced91",
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config.json
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The diff for this file is too large to render.
See raw diff
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runtime_audit.json
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{
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"applied_config_corrections": [
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{
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"field": "quantization.mode",
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"new": "mxfp8",
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"old": "affine",
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"physical_evidence_consistent": true
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},
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{
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"field": "quantization_config.mode",
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"new": "mxfp8",
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"old": "affine",
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"physical_evidence_consistent": true
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}
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],
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"current_config_sha256": "b49450c5c373f46fa637822bbbd466ada245fb3b58c40e589d41a8932070670f",
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"date": "2026-10-06",
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"header_sha256": {
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"model.safetensors": "d6b3f9419188abb3890994fbfd1f6982179b14b3a634951169520b52e46d2fdb"
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},
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"input_bindings": {
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"axquant_manifest.json": "fbb3ac237972ada8e6f5d7d4f7f7c13aff9c346d18cd8b96a7ef6b6d45aa5944",
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"config.json": "3aeb949fad423de8a2d7c0c6d9bb52baf18a1c92e72b5761040f31ff1a3eebd0",
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"model.safetensors.index.json": "6ec8c2db4004f31b9d945957229ba7619a59734e07778e42e70c4b583880a88f"
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},
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"issues": [],
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"model_type": "qwen3",
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"mtp_files": [],
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"ngram_action": "none; do not invent n-gram data",
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"ngram_files": [],
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"ngram_quantization": [],
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"ngram_table_metadata": null,
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"ngram_tensor_count": 0,
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"quality_certified": false,
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"quantization": {
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"quantization": {
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"container_mode": "affine",
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"per_module_modes": {
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"mxfp8": 197
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},
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"physical_recipe_issues": []
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},
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"quantization_config": {
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"container_mode": "affine",
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"per_module_modes": {
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"mxfp8": 197
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},
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"physical_recipe_issues": []
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}
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},
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"removed_source_evidence": [],
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"repo_id": "AutomatosX/AX-Qwen3-Embedding-0.6B-MLX-AXQ-MXFP8",
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"runtime_arch_id": null,
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"runtime_verified": false,
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"schema_version": "axquant.hub-runtime-audit.v1",
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"scope": "Pinned remote config/index/Safetensors header audit; no runtime load or generation claim.",
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"source_revision": "dadc5445b6069b0179c323f11ec93026942cb622",
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"status": "no-audited-peer-export-profile",
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"unchanged_weight_sha256": {
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"model.safetensors": "4ff6f3b73633a5194cf0ba50b944789466eb47a4a2b199f5db8944a566fd22d8"
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}
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}
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