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README.md

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+---
+library_name: coreai
+pipeline_tag: text-classification
+base_model: vllm-sr/lora_intent_classifier_bert-base-uncased_model
+license: apache-2.0
+---
+
+# lora_intent_classifier_bert-base-uncased_model-CoreAI — Apple Core AI
+
+A Core AI (`.aimodel`) build of [`vllm-sr/lora_intent_classifier_bert-base-uncased_model`](https://huggingface.co/vllm-sr/lora_intent_classifier_bert-base-uncased_model) for on-device inference on Apple Silicon.
+
+Architecture: `BertForSequenceClassification`. Upstream ships PyTorch and no Core AI build.
+
+## Verified equivalence
+
+The exported graph and the repository's own PyTorch loader were run on identical inputs and the raw
+outputs diffed:
+
+| measure | value |
+|---|---|
+| worst absolute difference | 7.749e-06 |
+| output magnitude | 3.86 |
+| relative | 2.01e-06 |
+| minimum cosine | 1.0000000000 |
+
+Arithmetic equivalence only — **no quality benchmark here**: no F1, no accuracy score, and no claim
+against upstream's published numbers. The probes are the converter's default set; they exercise the
+graph rather than demonstrating the model doing its job.
+
+## Built by
+
+[ahmedandaloes](https://huggingface.co/ahmedandaloes) — Apple Silicon builds (Core AI, MLX, GGUF) for
+models that ship none, each machine-checked against its own reference.
+**[ahmedandaloes.com](https://ahmedandaloes.com)**