Instructions to use groxaxo/Nemotron-3-Embed-1B-oQ4-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
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How to use groxaxo/Nemotron-3-Embed-1B-oQ4-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Nemotron-3-Embed-1B-oQ4-MLX groxaxo/Nemotron-3-Embed-1B-oQ4-MLX
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Nemotron-3-Embed-1B-oQ4-MLX
Overview
Nemotron-3-Embed-1B-oQ4-MLX is an MLX-formatted checkpoint optimized for Apple silicon, published by groxaxo.
It is intended for open-source evaluation, reproducible experimentation, and compatible local or
hosted inference workflows. The wording below is deliberately limited to what can be verified
from this repository's metadata and artifacts.
At a glance
| Field | Details |
|---|---|
| Format | MLX |
| Source / base | nvidia/Nemotron-3-Embed-1B-BF16 |
| Intended task | feature-extraction |
| License | other |
What is included
*.safetensors(1 file)config.jsontokenizer.jsontokenizer_config.json- Additional configuration, tokenizer, processor, or shard files (14 visible artifacts total)
Quick start
MLX
Use an up-to-date MLX-compatible runtime on Apple silicon and point it at this repository:
mlx_lm.generate --model groxaxo/Nemotron-3-Embed-1B-oQ4-MLX --prompt "Write a concise technical summary."
Embedding and audio repositories may require the task-specific MLX package documented by the upstream project.
Compatibility and responsible use
- Use a runtime that explicitly supports this format, architecture, and modality.
- Keep configuration, tokenizer, processor, projection, and weight files from the same revision together.
- Review the source model card and license before redistribution or deployment.
- Hardware needs depend on parameter count, context length, cache precision, quantization, and concurrency.
- Report reproducible issues with the runtime version, hardware, launch command, and a minimal example.
Quantization or conversion changes numerical behavior, memory use, and throughput relative to the source checkpoint; validate quality on your own workload.
Generated outputs may be inaccurate or unsuitable for a given use case. Users are responsible for testing behavior, applying appropriate safeguards, and complying with applicable licenses and laws.
An Apple-Silicon-native OMLX oQ4 conversion of
nvidia/Nemotron-3-Embed-1B-BF16.
This derivative was produced locally on Apple Silicon with the same streaming, sensitivity-driven OMLX pipeline used for the oQ5 release. It uses a base 4-bit affine plan, group size 64, and bfloat16 working dtype. The calibration ran on the checkpoint's bidirectional encoder architecture rather than through a causal-LM wrapper. No weights were retrained.
The quantized safetensors payload is 670,214,436 bytes. OMLX promoted 26 sensitivity-selected projections to 5, 6-bit precision.
Embedding contract
- bidirectional attention (
is_causal: false) - average/mean pooling
- L2-normalized 2,048-dimensional output
query:prefix for queriespassage:prefix for documents
BF16 fidelity smoke test
The source and this oQ4 checkpoint were evaluated using a query, a matching passage, and an unrelated passage. All outputs were 2,048-dimensional and L2-normalized.
| Input | BF16 to oQ4 vector cosine |
|---|---|
| Query | 0.992316 |
| Related passage | 0.993071 |
| Unrelated passage | 0.991795 |
| Comparison | BF16 | oQ4 |
|---|---|---|
| Query to related passage | 0.680575 | 0.693227 |
| Query to unrelated passage | -0.024595 | -0.013228 |
Quick start on Apple Silicon
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade mlx mlx-lm transformers huggingface_hub
hf download groxaxo/Nemotron-3-Embed-1B-oQ4-MLX --local-dir ./Nemotron-3-Embed-1B-oQ4-MLX
python ./Nemotron-3-Embed-1B-oQ4-MLX/embed_mlx.py \
--model ./Nemotron-3-Embed-1B-oQ4-MLX \
--query "Which city is known as the City of Sails?" \
--passage "Auckland is widely known as the City of Sails."
The included script deliberately loads the bare Ministral3 backbone and
applies non-causal attention. The regular MLX-LM generation path is causal and
is not the correct embedding interface for this checkpoint.
Quantization details
| Setting | Value |
|---|---|
| OMLX source revision | a534507fb5ab760d239283868a4c790386b316ff |
| Base model revision | a5e0f804b9e90a1ca6784ecbf6e41595774fc834 |
| OMLX level | oQ4 |
| Base quantization | 4-bit affine |
| Group size | 64 |
| Working dtype | bfloat16 |
| Calibration | 128 samples × 256 tokens |
| Sensitivity-selected boosts | 26 |
See QUANTIZATION_REPORT.md for artifact SHA-256 values and the full local
validation result.
License
This derivative inherits the
OpenMDW-1.1
license from the source model. LICENSE, NOTICE, and
THIRD_PARTY_NOTICES.md are included unchanged from NVIDIA's source
repository.
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Base model
mistralai/Ministral-3-3B-Base-2512