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Publish AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4

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.gitattributes CHANGED
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README.md ADDED
@@ -0,0 +1,176 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ library_name: mlx
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+ base_model: nvidia/Nemotron-3-Embed-1B-BF16
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+ base_model_relation: quantized
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+ pipeline_tag: feature-extraction
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+ tags:
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+ - mlx
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+ - apple-silicon
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+ - quantized
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+ - mixed-precision
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+ - axquant
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+ - axq
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+ - development
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+ - mistral3
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+ - MXFP4
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+ - MXFP4
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+ - embedding
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+ - sentence-similarity
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+ ---
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+
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+ # AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4 — 5.25 BPW measured main
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+
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+ An **AXQuant (AXQ)** mixed-precision MLX checkpoint for Apple Silicon, converted directly from
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+ the BF16 source model. The language path is quantized under AXQuant protection floors (embeddings, norms, and other protected tensors remain higher precision).
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+
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+ > **Development evidence — not a certified AXQuant release.** This package has conversion and
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+ > artifact-integrity records, but it does not publish measured quality, long-context, kernel-speed,
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+ > or MTP-speed evidence. Do not interpret the AXQ product label as a benchmark claim.
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+
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+
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+ ## Model details
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+
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+ | Property | Value |
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+ | --- | --- |
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+ | Base model | [nvidia/Nemotron-3-Embed-1B-BF16](https://huggingface.co/nvidia/Nemotron-3-Embed-1B-BF16/tree/c0c9fea93ea424587517f2c59e20db9f1d6bf615) |
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+ | Source revision | `c0c9fea93ea424587517f2c59e20db9f1d6bf615` |
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+ | Product family | `mistral3` |
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+ | Source architecture | `Ministral3Model` (dense); text path optimized |
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+ | Main-model parameters | 1.14B logical parameters |
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+ | Quantizer | AXQuant `1.9.0` |
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+ | Hub budget class | `MXFP4` |
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+ | AXQuant base precision class | `8bit` |
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+ | Planned storage-adjusted BPW | 5.8241 |
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+ | Measured main-model BPW | 5.2508 |
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+ | Measured total BPW | **5.2508** |
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+ | Safetensors weight size | 0.75 GB |
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+ | Approximate complete download | 0.77 GB |
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+ | Configured maximum context | 262,144 tokens; practical limits depend on unified memory |
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+ | Primary MLX runtime | MLX-LM |
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+ | AX Engine native execution | Not established; no validated native manifest is included |
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+ | MTP present | `False` |
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+ | Vision present | `False` |
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+ | Audio present | `False` |
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+
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+ This repository contains MLX Safetensors. It does **not** contain PyTorch or GGUF weights.
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+
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+ ## Choosing an AXQ pack
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+
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+ AXQ names describe a **storage-budget product class**, not one uniform precision applied to every
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+ tensor. Protected tensors remain at higher precision, so the exact measured BPW is authoritative.
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+ In particular, a `6bit`-named mixed plan may retain `4bit` as its base precision while selecting
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+ 6-bit, 8-bit, or BF16 for other tensors to meet an approximately 6-BPW total budget. Protection
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+ floors can also raise a `4bit`-named pack close to (or above) a `6bit` budget on small or heavily
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+ protected models. When that collapse happens, AutomatosX does **not** publish a separate
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+ misleading `4bit` sibling for that base.
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+
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+
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+ | Sibling | Intended trade-off |
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+ | --- | --- |
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+ | [4bit sibling](https://huggingface.co/AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-4bit) | Lower-storage AXQ budget; check its exact BPW |
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+ | [8bit sibling](https://huggingface.co/AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-8bit) | Higher average precision near the 8-BPW budget |
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+
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+ See the [AutomatosX collections](https://huggingface.co/AutomatosX/collections)
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+ for the family catalog, or the [complete index](https://huggingface.co/collections/AutomatosX/automatosx-mlx-model-catalog).
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+
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+ ## Download
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+
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+ ```bash
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+ python -m pip install -U huggingface_hub
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+ hf download AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4 --local-dir ./AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4
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+ ```
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+
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+ Allow at least 0.77 GB of free disk space. Pin the resulting Hub commit in reproducible
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+ deployments rather than relying indefinitely on `main`.
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+
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+ ## Run with MLX-LM
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+
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+ ```bash
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+ python -m pip install -U mlx-lm
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+ mlx_lm.generate \
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+ --model AutomatosX/AX-Nemotron-3-Embed-1B-MLX-AXQ-MXFP4 \
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+ --prompt "Explain mixed-precision quantization in three sentences." \
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+ --max-tokens 128 \
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+ --temp 0.0
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+ ```
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+
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+ MLX-LM compatibility covers standard **text/backbone inference**. It may ignore AXQuant runtime
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+ metadata and optional sidecars (`vision.safetensors`, `mtp.safetensors`); this command therefore
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+ does not establish MTP acceleration or vision-language quality. The artifact records MLX
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+ `0.32.1` and MLX-LM `0.31.3` from conversion.
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+
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+ ## AX Engine status
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+
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+ This package does **not** include a validated native `model-manifest.json`, so AX Engine execution
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+ is not established by this release. The AX Engine fields in `axquant_runtime.json` describe the
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+ intended compatibility contract, not observed runtime evidence. Use the architecture-specific MLX
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+ runtime path above. The artifact records AX Engine version
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+ `7.5.7`, but version discovery alone is not a runtime check.
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+
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+
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+ ## Quantization layout
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+
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+ | Main-weight precision | Parameters | Share |
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+ | --- | ---: | ---: |
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+ | `4bit` | 872.42M | 76.47% |
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+ | `8bit` | 268.44M | 23.53% |
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+ | `bf16` | 67,584 | 0.01% |
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+
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+ - Quantization methods: `affine, bf16, mxfp4`.
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+ - Group sizes used by quantized assignments: `32, 64`.
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+ - MTP sidecar: not included.
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+ - Vision sidecar: not included.
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+ - Optimization scope: `text-path`.
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+ - Support tier: `convertible`.
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+
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+ BF16 sidecars, when present, are included in total download size. Their presence does not by itself
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+ establish MTP acceleration or vision-language quality.
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+
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+ ## Evidence and validation status
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+
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+ | Check | Status |
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+ | --- | --- |
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+ | Planning evidence | `architecture_prior` |
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+ | Calibration | none; the allocation is based on architecture priors |
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+ | Quantizer execution | 113/113 recorded module conversions succeeded; 0 fallbacks |
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+ | AX Engine native manifest | not included |
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+ | Quality versus BF16 or uniform baselines | Not published; no quality-retention claim |
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+ | MTP acceptance and speed | not measured; no MTP speedup claim |
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+ | AX Engine kernel evidence | `unmeasured` |
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+ | Vision-language quality | Not applicable (no vision tower in this package) |
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+ | Speech-recognition quality | Not applicable |
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+ | Long-context quality | 262,144-token capacity is config metadata, not a validated claim |
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+ | Release certification | **Not certified**; formal AXQuant M0-M8 gates are not closed |
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+
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+ ## Intended use and limitations
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+
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+ - Intended for local development and evaluation on Apple Silicon with MLX-compatible runtimes.
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+ - No minimum unified-memory figure is claimed; loadability depends on model size, context length,
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+ KV-cache policy, runtime buffers, and other processes using unified memory.
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+ - Architecture-prior allocation is not measured sensitivity. It must not be presented as measured
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+ model quality.
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+ - The configured context window can require substantially more memory as the KV cache grows.
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+ - AX Engine execution is not established because this package has no validated native manifest.
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+
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+ - Upstream capabilities, limitations, biases, and responsible-use guidance still apply.
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+
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+ ## Provenance and audit files
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+
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+ - [`axquant_manifest.json`](axquant_manifest.json): package identity, byte accounting, runtime
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+ contract, software versions, and file checksums.
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+ - [`axquant_plan.json`](axquant_plan.json): per-tensor precision decisions and planning evidence.
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+ - [`axquant_quantizer_execution.json`](axquant_quantizer_execution.json): conversion coverage and
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+ fallback records.
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+ - [`axquant_runtime.json`](axquant_runtime.json): declared AX Engine and MLX compatibility metadata; runtime checks remain separate evidence.
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+
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+ All published provenance uses repository-relative paths. Local source paths are stripped before
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+ publication. The checkpoint was converted from BF16 rather than re-quantized from an OptiQ
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+ artifact. If an OptiQ repository is published separately, it uses a different quantizer and
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+ should not be assumed to have identical BPW or quality.
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+
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+ ## License
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+
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+ The checkpoint follows the upstream model license where applicable (often Apache License 2.0). See
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+ the [nvidia/Nemotron-3-Embed-1B-BF16 model card](https://huggingface.co/nvidia/Nemotron-3-Embed-1B-BF16/tree/c0c9fea93ea424587517f2c59e20db9f1d6bf615) for license terms, model
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+ limitations, and responsible-use guidance.
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axquant_runtime.json ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "name": "mlx-lm",
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+ "<SPECIAL_991>",
998
+ "<SPECIAL_992>",
999
+ "<SPECIAL_993>",
1000
+ "<SPECIAL_994>",
1001
+ "<SPECIAL_995>",
1002
+ "<SPECIAL_996>",
1003
+ "<SPECIAL_997>",
1004
+ "<SPECIAL_998>",
1005
+ "<SPECIAL_999>"
1006
+ ],
1007
+ "is_local": true,
1008
+ "local_files_only": false,
1009
+ "model_max_length": 32768,
1010
+ "pad_token": "<pad>",
1011
+ "padding_side": "left",
1012
+ "tokenizer_class": "TokenizersBackend",
1013
+ "unk_token": "<unk>"
1014
+ }