Add loose sherpa-onnx layout files (no tar.bz2 extraction needed)

Byte-identical copies of the four sherpa-onnx runtime files plus bpe.vocab, LICENSE-WEIGHTS and NOTICE.md from onnx/sherpa-onnx-orukeet-v0.1.0-int8.tar.bz2, stored uncompressed for clients that cannot extract tar.bz2 (iOS). All SHA-256 digests match onnx/manifest.json.

onnx/sherpa-loose-v0.1.0-int8/LICENSE-WEIGHTS

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onnx/sherpa-loose-v0.1.0-int8/NOTICE.md

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+# Attribution and license scope
+
+Orukeet is an adaptation of **NVIDIA Parakeet TDT 0.6B v3**. NVIDIA retains
+copyright in its model and upstream work. The base weights are distributed
+under [CC BY 4.0](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3).
+Oruk AI's changes comprise multilingual/accent continuation training, parameter
+blending, fitted and frozen Gabor-kernel replacement and recovery, native and ONNX
+export, application integration and evaluation. [Model stages](https://github.com/Oruk-AI/orukeet/blob/main/release/model-stages.json)
+identifies r3 as the source of every current Orukeet download and records its ancestry.
+
+The r3 NeMo, ONNX INT8, Q8 GGUF and F16 GGUF weights, and their fitted Gabor kernels,
+are designated **CC BY-SA 4.0**.
+The complete license is in [LICENSE-WEIGHTS](LICENSE-WEIGHTS). This permits
+commercial use and modification, with attribution and applicable ShareAlike
+requirements. Earlier checkpoints retain their source notices and are not
+silently relicensed by this file. Orukeet v0.1.0 distributes the final r3 checkpoint in all four formats.
+
+Python and integration code in this repository is MIT unless a file specifies
+otherwise. The native bindings, audio windowing and worker transport derive
+from OpenWhisper by Knuckles92 and its Oruk AI integration; their MIT notice is
+retained in [LICENSE](LICENSE). The downloaded NVIDIA NeMo-Speech.cpp SDK and
+its bundled dependencies retain their own notices, including Apache-2.0 and
+MIT components. Keep the SDK's license files when redistributing it. The
+[pinned source](https://github.com/NVIDIA/NeMo-Speech.cpp/tree/4f9676226f667d14608487df744f375db87127f8)
+is the authority for those terms.
+
+The ONNX exporter follows sherpa-onnx's Parakeet TDT v3 conversion script.
+Its upstream reference and Apache-2.0 license are retained in
+[export/onnx](export/onnx/README.md). The ONNX archive includes the weight
+license and source attribution.
+
+Training data credits:
+
+- Mozilla/Common Voice contributors: Common Voice 22, CC0.
+- Google and the FLEURS authors: FLEURS, CC BY 4.0.
+- Google and the OpenSLR 83 authors, with the `ylacombe/english_dialects`
+  restructuring: English dialect speech, CC BY-SA 4.0.
+- Beijing Kingline Data Technology and the SpeechOcean762 authors:
+  SpeechOcean762, CC BY 4.0.
+- SpeechColab and the GigaSpeechBench authors: 17 English accent/domain splits
+  in the final continuation. Their paper identifies Creative Commons source audio;
+  the source record below preserves the available license details.
+- DISCO at ETH Zurich and the EuroSpeech contributors: Bulgarian, Greek and
+  Italian parliamentary speech, with the providers' country-specific terms.
+- SberDevices and the Golos authors: Golos Crowd, under the
+  [Public license with attribution and conditions reserved](https://github.com/sberdevices/golos/blob/master/license/en_us.pdf).
+- Nordisk Språkteknologi, the National Library of Norway and the Alexandra
+  Institute: NST Swedish and Danish, distributed under CC0.
+- ILSP/Athena Research Center and the Lesbian Speech Corpus contributors:
+  dialect speech from Lesbos. The source card does not specify a reuse license.
+
+Data were filtered, split, normalized and sampled as described in
+[data and licenses](https://github.com/Oruk-AI/orukeet/blob/main/docs/data-and-licenses.md). Corpus copyrights and source
+terms remain with their owners. Evaluation-only data have separate terms.
+No endorsement by NVIDIA, Mozilla, Google or the other source projects is implied.
+
+The generated statistical records in `evidence/metric-evidence.tar.gz`, the
+Gabor recovery count bundles under `training/gabor_half/results/`, and the
+FT-4035 benchmark counts under `evidence/regression-ft-20260907/` are
+designated CC BY 4.0, attributed to Oruk AI. This designation covers the
+prepared metric records; it does not relicense the original corpus recordings
+or transcripts, which are not included in that archive.
+
+The r3 numeric benchmark records in `evidence/standard-asr-r3-20260908/` and
+`evidence/domains-r3-20260908/` are released under CC BY 4.0. They contain
+error counts and recording identifiers; dataset audio remains with its providers.
+
+The paired ONNX application benchmark counts in `evidence/onnx-r3-20260910/`
+are also released under CC BY 4.0. These records contain numeric errors,
+timings and recording identifiers, without corpus audio or transcripts.
+
+## ONNX depthwise execution
+
+The sherpa-onnx INT8 package includes a deterministic graph optimization of r3.
+Twenty-four nine-tap depthwise integer convolutions are evaluated using centered
+FP32 convolution and cast back to INT32 before the original dequantization.
+The original quantized tensors, zero points, scales, tokenizer and TDT interface
+are retained. No model training or new inference dependency is introduced.
+
+Each centered input and weight lies between -255 and 255. A nine-tap partial
+sum has magnitude at most 585,225, within FP32's exact integer range. Recorded
+operator and complete-encoder comparisons using ONNX Runtime 1.27.0 produce
+bit-identical outputs. The optimizer and its conversion evidence are available
+in [Orukeet's repository](https://github.com/Oruk-AI/orukeet/tree/main/evidence/speed20260910).
+The model weight license remains CC BY-SA 4.0.

onnx/sherpa-loose-v0.1.0-int8/README.md

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+# Orukeet v0.1.0 INT8 — sherpa-onnx layout, loose files
+
+The same four runtime files as `onnx/sherpa-onnx-orukeet-v0.1.0-int8.tar.bz2`, stored
+uncompressed so that clients which cannot extract `tar.bz2` can fetch them directly.
+
+**Nothing here is modified.** Every file is byte-identical to the archive member of the
+same name; the SHA-256 digests below are the ones published in `onnx/manifest.json`.
+
+| File | Bytes | SHA-256 |
+|:--|--:|:--|
+| `encoder.int8.onnx` | 653,182,378 | `7b55f2a504a20a8e462899f5befd45f4a1784948d76ed0127902d9cf39405487` |
+| `decoder.int8.onnx` | 11,845,332 | `c185c2afb4c77c94bb1314807ecb3dc1623057a3dc540b83e10301af9bf4cfca` |
+| `joiner.int8.onnx` | 6,355,335 | `1a7e90abf7172d926dd7e2edac2a5d5035c24dfb641a15e131d57b6a5f63cdd3` |
+| `tokens.txt` | 93,939 | `d58544679ea4bc6ac563d1f545eb7d474bd6cfa467f0a6e2c1dc1c7d37e3c35d` |
+| `bpe.vocab` | 117,408 | `41d5e71b3591642eff088151efd7acd4e750124cc0054c8ba9fa3245187a4804` |
+
+Total: 671,619,800 bytes, matching the archive's extracted size.
+
+## Why this directory exists
+
+iOS has no `tar` and no bzip2 decompressor in this project's dependency set, so the
+published `.tar.bz2` cannot be unpacked on device. Fetching the members individually
+removes the need for an extraction step and for the temporary double allocation that
+extraction would require.
+
+`onnx/combined-v0.1.0-int8/` is **not** a substitute: its `decoder_joint-model.int8.onnx`
+fuses the decoder and joiner into one graph for Parakeet-compatible Rust engines, and
+sherpa-onnx's offline transducer loader requires them separate. Its
+`encoder-model.int8.onnx`, `vocab.txt` and `bpe.vocab` are, however, the same bytes as
+the corresponding files here.
+
+## Use
+
+Identical to the archive — see `onnx/README.md`. Point sherpa-onnx's offline transducer
+loader at the four files:
+
+```python
+recognizer = sherpa_onnx.OfflineRecognizer.from_transducer(
+    encoder="encoder.int8.onnx",
+    decoder="decoder.int8.onnx",
+    joiner="joiner.int8.onnx",
+    tokens="tokens.txt",
+    model_type="nemo_transducer",
+    sample_rate=16000,
+    feature_dim=128,
+    decoding_method="greedy_search",
+)
+```
+
+The encoder's `url` metadata (`https://huggingface.co/oruk/orukeet#parakeet-tdt-v3`) is
+preserved, as the upstream export instructions require.
+
+## Provenance and license
+
+Repackaged from `onnx/sherpa-onnx-orukeet-v0.1.0-int8.tar.bz2` of this repository, which
+mirrors [oruk/orukeet](https://huggingface.co/oruk/orukeet) at revision
+`55a984d46f68323301837194ce647c702f55facc`. Archive SHA-256
+`f9191f30178cc9122ce2f023bf9fefafc822028307b0efa4caff645ba3fe8d0a`, verified before and
+after extraction.
+
+Weights: **CC BY-SA 4.0**, retaining NVIDIA's attribution for Parakeet TDT 0.6B v3.
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