Document retained MLX release provenance, license, checksums and validation limits

LICENSE

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PROVENANCE.json

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+{
+  "release_format": "MLX 6-bit affine, group size 64",
+  "weights_unchanged_from_revision": "3e2e03c8aa8f2afffa407e90c7c2b443ecaf676f",
+  "base_model": "Qwen/Qwen3.5-4B",
+  "base_snapshot_revision": "not recorded in retained training configuration",
+  "training_method": "LoRA on quantized 4-bit base; retained floating-point fusion followed by 6-bit quantization",
+  "native_unquantized_base_precision": false,
+  "retained_floating_source_sha256": {
+    "model-00001-of-00002.safetensors": "5da9935a53daa73bf22809a0f89165e8d4406328ecfd6b8c3ac3f38c137c1a56",
+    "model-00002-of-00002.safetensors": "01af619b9a984635330554b09cb45b652673230d55aa568a76d09449f7d066e8"
+  },
+  "published_model_sha256": "7d5f5d49a553d2dbeacbae56c72d69cbd3e828ee5cde4822637b1c2029fa5ac4",
+  "audited_dense_tensors": 426,
+  "audited_published_tensors": 924,
+  "requantized_tensor_equality": true,
+  "matrices_not_equal_to_sixbit_dequantization": 249,
+  "training_dataset_public": false,
+  "inference_hardware_verified": "Apple M5 Pro MacBook Pro, 48 GB, LM Studio MLX",
+  "nvidia_cuda_inference_verified": false,
+  "amd_rocm_inference_verified": false
+}

README.md

@@ -87,7 +87,7 @@ Select one target language from `chinese`, `japanese`, `hindi`, or `arabic`, the
 | Primary task | Context-aware transliteration and script conversion |
 | License | Apache 2.0 |
 
-## Evaluation
+## Historical standalone evaluation
 
 The published model was tested with exact final-text matching. A result passes only when the complete output matches an accepted answer, including preserved English, punctuation, code, and spacing.
 
@@ -98,6 +98,31 @@ The published model was tested with exact final-text matching. A result passes o
 
 The reserved multilingual score measures exact agreement with its reference responses. Exact-match scoring is strict: a valid alternative spelling or wording can still count as a mismatch. Review ambiguous names, dialect terms, and very short fragments before sending them.
 
+## Product-pipeline validation
+
+On September 6, 2026, the unchanged published MLX weights were tested with UnimeType's production Convert prompts and evaluator, using LM Studio on an Apple M5 Pro MacBook Pro with 48 GB memory and a 16,384-token context setting.
+
+| Check | Result |
+| --- | ---: |
+| Fixed conversion suite, exact accepted output | 97 / 127 |
+| Conversational-context regression suite, valid-reference exact agreement | 12 / 71 |
+| Context-suite structure and protected-literal count checks | 74 / 76 |
+| Protected-literal count and order, cases containing protected literals | 31 / 32 |
+
+These are product-pipeline results, including input protection, output validation, and 20 local-route cases in the fixed suite. They are not raw-model accuracy. Five structurally invalid reference answers are excluded from context agreement, but all 76 cases remain in the structure check. Context references are model-generated and have not been reviewed by native speakers. These suites have been used during development and are not an independent blind benchmark.
+
+Known limitations include ambiguous short inputs, Arabic dialect and spelling variation, and context-related formatting errors. A Japanese regression case also failed to preserve punctuation and an emoji. NVIDIA CUDA, AMD ROCm, iOS, and Android inference have not been validated for this release. The historical standalone scores above use a different evaluation setup and should not be treated as interchangeable with this product-pipeline run.
+
+## Release provenance and files
+
+This repository contains the retained MLX 6-bit release. The model was fine-tuned with LoRA on a quantized 4-bit Qwen3.5-4B base, fused into a floating-point checkpoint, and then quantized to 6-bit MLX. Floating-point storage does not recover the original base model's pre-quantization precision.
+
+The retained floating-point checkpoint was audited against this release: its 426 tensors reproduce all 924 published tensors under 6-bit affine quantization. It is not a dequantization of the published 6-bit weights. See [PROVENANCE.json](PROVENANCE.json) for source hashes and [SHA256SUMS](SHA256SUMS) for public-file checksums.
+
+**训练数据集未公开。** The training dataset is not publicly released. This repository does not include training data, data-generation scripts, training code, or training logs.
+
+The base model uses [Apache 2.0](https://huggingface.co/Qwen/Qwen3.5-4B/blob/main/LICENSE). A copy is included in [LICENSE](LICENSE). No Transformers-format or GGUF release is included in this repository.
+
 ## About UnimeType
 
 [UnimeType](https://unimetype.com/) helps multilingual writers type naturally across languages and writing systems. Transliteration 4B is the dedicated local model behind that direction: focused on conversion, compact enough for local use, and designed around the way people actually mix languages in daily writing.

SHA256SUMS

@@ -0,0 +1,9 @@
+bbedc3fda3305820b977265f01b8619d87570a6739de3a5582c3464840f1e57a  LICENSE
+04552b04439c0ff111c26346981f0b310761c182252445af947d2979232128ba  PROVENANCE.json
+75bf45bcecf251f64c57f06e9b8c54b0c782edd6bd3a98f0a573132c33ccbb63  README.md
+ad22cb6365e58696ffc10f1fbfc5f09b8762d0486df899e8f18b0491906e0b21  chat_template.jinja
+41bc0101eb66fc8d2322fbec82763f41a7406b9f2d3d6f48f55c7c8a41c96e4b  config.json
+7d5f5d49a553d2dbeacbae56c72d69cbd3e828ee5cde4822637b1c2029fa5ac4  model.safetensors
+647bf47db0319c1b3d348a2906ee53b37b3096b7df768016f30f0a4ded80619b  model.safetensors.index.json
+87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4  tokenizer.json
+970d4874c33b6624b3b979e5c3e55b777e77c1e6a115e985b202c8225fc81afd  tokenizer_config.json