Note: this INT8 version of Minerva 1B base v1.0 has been quantized for inference on Intel CPU, Intel iGPU (Arc) via intel-extension-for-pytorch, Intel NPU (AI Boost on Core Ultra series) via OpenVINO.
Replication Recipe
The recommended way to reproduce this exact quantization is via the auto-round-pipeline — the same orchestration tool that produced this artifact.
Step 1 — Bootstrap the auto-round-pipeline
Set up a dedicated conda environment using the pipeline's setup.sh. Any of the install modes below produces an environment that can reproduce this quantization; pick the one that matches your goals:
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git clone https://git.epicdynamic.com/auto-round-pipelinecd auto-round-pipeline# Pinned PyPI wheel (fastest; matches what this pipeline used by default):bash setup.sh --pip-version 0.13.0# Or build from intel/auto-round at the same tag (byte-identical reproducibility):bash setup.sh --source-tag v0.13.0# Intel Arc iGPU acceleration (e.g. Core Ultra 185H) — append to either of the above:# ... --intel-xpu# NVIDIA / AMD opt-in: --cuda / --rocm
The script prints the resulting conda env name (something like auto-round-pipeline-v0.13.0[-src][-xpu|-cuda|-rocm]) at the end.
Step 2 — Quantize just this model
Activate the env that setup.sh created, then invoke the runner with the same job filters that produced this artifact:
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conda activate <env-name-printed-by-setup.sh>python runner.py \ --model 'sapienzanlp/Minerva-1B-base-v1.0' \ --quant 'INT8-gs64' \ --format auto_gptq \ --no-upload # drop this to also push to HuggingFace Hub
Step 3 — (Optional) standalone Python recipe
If you'd rather call auto-round directly without the orchestration wrapper, this is the exact call the pipeline made:
This quantized model comes with no warranty. It has been developed only for research purposes.
git clone https://git.epicdynamic.com/auto-round-pipelinecd auto-round-pipeline# Pinned PyPI wheel (fastest; matches what this pipeline used by default):bash setup.sh --pip-version 0.13.0# Or build from intel/auto-round at the same tag (byte-identical reproducibility):bash setup.sh --source-tag v0.13.0# Intel Arc iGPU acceleration (e.g. Core Ultra 185H) — append to either of the above:# ... --intel-xpu# NVIDIA / AMD opt-in: --cuda / --rocm
conda activate <env-name-printed-by-setup.sh>python runner.py \ --model 'sapienzanlp/Minerva-1B-base-v1.0' \ --quant 'INT8-gs64' \ --format auto_gptq \ --no-upload # drop this to also push to HuggingFace Hub
