edithatogo/lfm2.5-1.2b-intel-lora

LFM Intel LoRA Smoke Artifacts

This repository contains tiny synthetic artifacts for validating an Intel/OpenVINO LoRA optimization pipeline.

It does not contain full LiquidAI/lfm2.5-1.2b-instruct model weights. The current Windows environment blocks the IPEX-backed path, so the files here validate the mechanics of LoRA adapter training, ONNX export, OpenVINO IR conversion, INT8 quantization, and CPU inference latency on a small synthetic model.

Artifacts

• adapter_smoke.pt: synthetic LoRA adapter checkpoint from a 5-step smoke run
• smoke_result.json: smoke training metrics
• model.onnx: ONNX export of the tiny smoke model
• model.json: ONNX export metadata
• openvino-ir/model.xml: FP OpenVINO IR definition
• openvino-ir/model.bin: FP OpenVINO IR weights
• openvino-ir/model_ir.json: FP OpenVINO IR conversion metadata
• openvino-int8/model_int8.xml: INT8 OpenVINO IR definition
• openvino-int8/model_int8.bin: INT8 OpenVINO IR weights
• openvino-int8/model_int8_quantization.json: INT8 quantization metadata
• cpu_latency.json: CPU latency validation metrics

CPU Validation

Measured on CPU with 50 iterations after 5 warmups:

• FP mean latency: 0.053568 ms
• FP p95 latency: 0.065855 ms
• INT8 mean latency: 0.061286 ms
• INT8 p95 latency: 0.087240 ms
• Max FP-vs-INT8 absolute difference: 0.64642227
• INT8 predictions finite: true

Environment Notes

• openvino==2024.6.0
• openvino-dev==2024.6.0
• nncf==2.8.0
• onnx==1.21.0
• onnxscript==0.7.0

nncf==3.1.0 was incompatible with openvino==2024.6.0 in this environment because openvino.Node is not available. nncf==2.8.0 successfully produced the INT8 IR.

Intended Use

Use these files as a small reproducible smoke package for pipeline validation. Do not treat them as a real fine-tuned LFM checkpoint.

Access, versioning and use — 27 October 2026

Public repository with anonymous access. Public availability does not itself establish source reuse permission or completeness.

This pass reviewed repository metadata and the published artifact inventory only. It did not execute model weights, reproduce training or revalidate reported benchmark scores. Existing base-model, prompt, experimental and synthetic-smoke limitations remain authoritative.

The asset inventory was checked at revision 91f6077b131deb59b05845d4db689d60329ec774. Counts/status in source receipts apply to those editions and runs, not all upstream sources. Snapshots, candidates, fixtures and metadata-only products must not be represented as complete released datasets or clinically/operationally validated products.

Start with cpu_latency.json, model.json, openvino-int8/model_int8_quantization.json.

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