Add CoreML iOS15 NeuralNetwork fp16 streaming (Rizeh Pizeh v1.0)

README.md

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+---
+language:
+- fa
+license: cc-by-nc-4.0
+library_name: coreml
+pipeline_tag: automatic-speech-recognition
+base_model:
+- Reza2kn/Shenava-Rizeh-Pizeh-v1.0
+base_model_relation: quantized
+tags:
+- coreml
+- neuralnetwork
+- ios
+- ios15
+- ios14
+- persian
+- farsi
+- asr
+- fastconformer
+- streaming
+- ctc
+- fp16
+- on-device
+- shenava
+- shenava-1
+- visualears
+---
+
+# Shenava — Rizeh Pizeh v1.0 (6.9M) · CoreML iOS15 NeuralNetwork fp16
+
+CoreML **NeuralNetwork** (not ML Program) fp16 export of [`Reza2kn/Shenava-Rizeh-Pizeh-v1.0`](https://huggingface.co/Reza2kn/Shenava-Rizeh-Pizeh-v1.0) — built so **older Apple devices capped at iOS 15** (e.g. iPad Air 2 / iOS 15.8) can load and run it. ML Program packages require iOS 16+; this targets **NeuralNetwork / CoreML spec v5 with iOS 14 availability**, so it runs on iOS 15.
+
+This is the **cache-aware streaming** step (one 170 ms prediction), the same kind of artifact as [`shenava-fa-fastconformer-streaming-32m-coreml-ios15-fp16`](https://huggingface.co/Reza2kn/shenava-fa-fastconformer-streaming-32m-coreml-ios15-fp16).
+
+## The Shenava-1 family (CoreML iOS15)
+
+- [`Shenava-Koochik-1.0-CoreML-iOS15-fp16`](https://huggingface.co/Reza2kn/Shenava-Koochik-1.0-CoreML-iOS15-fp16) — **Koochik 1.0** (114M) · teacher / flagship
+- [`Shenava-Rizeh-v1.0-CoreML-iOS15-fp16`](https://huggingface.co/Reza2kn/Shenava-Rizeh-v1.0-CoreML-iOS15-fp16) — **Rizeh v1.0** (32M) · mid-tier
+- [`Shenava-Rizeh-Pizeh-v1.0-CoreML-iOS15-fp16`](https://huggingface.co/Reza2kn/Shenava-Rizeh-Pizeh-v1.0-CoreML-iOS15-fp16) — **Rizeh Pizeh v1.0** (6.9M) · tiniest
+
+## Benchmark — fair WER/CER (parent model, decoded @ `[70,13]`)
+
+| Member | golden-6669 WER | CER | FLEURS-fa WER | CER |
+|---|---|---|---|---|
+| **Rizeh Pizeh v1.0 (6.9M)** | **24.55%** | 8.89% | **26.95%** | 10.22% |
+
+## CoreML contract (cache-aware streaming CTC step, att_context `[70,0]`)
+
+Inputs:
+- `processed_signal`: `Float32 [1, 80, 17]`
+- `cache_last_channel`: `Float32 [12, 1, 70, 144]`
+- `cache_last_time`: `Float32 [12, 1, 144, 8]`
+
+Outputs:
+- `logits`: `Float32 [1, 1, 1025]`
+- `cache_last_channel_next`: `Float32 [12, 1, 70, 144]`
+- `cache_last_time_next`: `Float32 [12, 1, 144, 8]`
+
+Streaming geometry: feature_frames per prediction = **17** (pre_encode_cache 9 + chunk 8), audio window **170 ms**, constant cache length **70**, `d_model=144`, `12` conformer layers, ×8 subsampling (80 ms/frame).
+
+## Compatibility (Xcode `coremlc`)
+
+- model type: `MLModelType_neuralNetwork`
+- storage precision: `Float16`
+- specification version: `5`
+- availability: `iOS 14.0`, `macOS 11.0`
+
+```bash
+coremlc compile shenava_rizeh_pizeh_v1_0_ctc_streaming_att70_0_ios15_fp16.mlmodel /tmp/out --deployment-target 15.0 --platform ios
+```
+
+## Files
+
+- `shenava_rizeh_pizeh_v1_0_ctc_streaming_att70_0_ios15_fp16.mlmodel` — fp16 NeuralNetwork model (~14 MB)
+- `tokens.json`, `preprocessor.json`, `mel_filters_slaney_80x257.json` — sidecars (ve_tok_v4, shared across the family)
+- `shenava_rizeh_pizeh_v1_0_ctc_streaming_att70_0_ios15_fp16_manifest.json` — export manifest
+- `export_koochik10_streaming_coreml.py` — reproducible export script
+
+Tokenizer: ve_tok_v4 (SentencePiece BPE-1024 +blank, digit/punct/«»-aware). Numbers are emitted in **spoken form**; apply Persian ITN at display for digits. Part of [VisualEars / Shenava](https://shenava.app).
+
+Export stack: coremltools 9.0, torch 2.7.0, NeMo 2.7.3. fp16 vs fp32 argmax agreement: **1.000**.

export_koochik10_streaming_coreml.py

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+#!/usr/bin/env python3
+"""Export Shenava Koochik 1.0 (114.8M) true cache-aware streaming CTC step to CoreML.
+
+One cache-aware encoder step + auxiliary CTC head, as an iOS14-target CoreML
+NeuralNetwork (valid on iOS15+; ANE-friendly on modern iPhones), fp16 weights —
+the same proven path as the deployed 32M staticmask model.
+
+  processed_signal [1,80,feature_frames] + caches -> logits + next caches
+
+feature_frames is derived correctly as pre_encode_cache_size + chunk_size (NOT the
+stale shift+2 formula): e.g. att[70,1] -> 9+16 = 25, matching the deployed 32M Swift.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import time
+import types
+from pathlib import Path
+
+import coremltools as ct
+from coremltools.models.neural_network import quantization_utils
+import nemo.collections.asr as nemo_asr
+import numpy as np
+import torch
+
+
+def install_static_full_cache_masks(encoder, att_context: list[int]) -> None:
+    """Freeze mask creation for the steady-state full-cache streaming step.
+
+    The traced graph always feeds a full feature chunk and a full left-cache.
+    NeMo's generic mask builder uses dynamic shape ops the CoreML NeuralNetwork
+    frontend chokes on; this emits equivalent constant masks for that fixed case.
+    """
+
+    def _static_create_masks(self, att_context_size, padding_length, max_audio_length, offset, device):
+        total = int(max_audio_length)
+        rows = torch.arange(total, device=device).view(total, 1)
+        cols = torch.arange(total, device=device).view(1, total)
+        left, right = int(att_context[0]), int(att_context[1])
+        if self.att_context_style == "chunked_limited":
+            chunk_size = right + 1
+            row_chunk = torch.div(rows, chunk_size, rounding_mode="trunc")
+            col_chunk = torch.div(cols, chunk_size, rounding_mode="trunc")
+            diff_chunks = row_chunk - col_chunk
+            left_chunks = left // chunk_size if left >= 0 else 10000
+            allowed = torch.logical_and(diff_chunks <= left_chunks, diff_chunks >= 0)
+        else:
+            allowed = torch.ones((total, total), dtype=torch.bool, device=device)
+            if left >= 0:
+                allowed = torch.logical_and(allowed, cols >= rows - left)
+            if right >= 0:
+                allowed = torch.logical_and(allowed, cols <= rows + right)
+        att_mask = torch.logical_not(allowed).unsqueeze(0)
+        pad_mask = torch.zeros((1, total), dtype=torch.bool, device=device)
+        return pad_mask, att_mask
+
+    encoder._create_masks = types.MethodType(_static_create_masks, encoder)
+
+
+class StreamingCTCStep(torch.nn.Module):
+    def __init__(self, model, att_context: list[int], feature_frames: int, constant_cache_len: int, local_attn: bool):
+        super().__init__()
+        self.encoder = model.encoder
+        # Hybrid RNNT/CTC models expose the CTC head as `ctc_decoder`; pure-CTC
+        # models (the smallest student) expose it as `decoder`.
+        self.ctc_decoder = getattr(model, "ctc_decoder", None) or model.decoder
+        self.encoder.change_attention_model(
+            self_attention_model="rel_pos_local_attn" if local_attn else None,
+            att_context_size=att_context,
+            update_config=False,
+            device=torch.device("cpu"),
+        )
+        self.encoder.setup_streaming_params(att_context_size=att_context)
+        self.feature_frames = int(feature_frames)
+        self.constant_cache_len = int(constant_cache_len)
+
+    def forward(self, processed_signal, cache_last_channel, cache_last_time):
+        processed_signal_length = processed_signal.new_full((1,), self.feature_frames, dtype=torch.int64)
+        cache_last_channel_len = processed_signal.new_full((1,), self.constant_cache_len, dtype=torch.int64)
+        encoded, _encoded_len, next_channel, next_time, _next_len = self.encoder.cache_aware_stream_step(
+            processed_signal=processed_signal,
+            processed_signal_length=processed_signal_length,
+            cache_last_channel=cache_last_channel,
+            cache_last_time=cache_last_time,
+            cache_last_channel_len=cache_last_channel_len,
+            keep_all_outputs=False,
+        )
+        logits = self.ctc_decoder(encoder_output=encoded)
+        return logits, next_channel, next_time
+
+
+def package_size(path: Path) -> int:
+    return sum(p.stat().st_size for p in path.rglob("*") if p.is_file()) if path.is_dir() else path.stat().st_size
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--nemo", required=True, type=Path)
+    ap.add_argument("--out-dir", required=True, type=Path)
+    ap.add_argument("--att-context", default="70,1")
+    ap.add_argument("--name", required=True)
+    ap.add_argument("--local-attn", action="store_true", help="use rel_pos_local_attn instead of static-mask full attention")
+    ap.add_argument("--keep-fp32", action="store_true")
+    args = ap.parse_args()
+
+    att_context = [int(x.strip()) for x in args.att_context.split(",")]
+    out_dir = args.out_dir.expanduser().resolve()
+    out_dir.mkdir(parents=True, exist_ok=True)
+    local_attn = bool(args.local_attn)
+
+    print(f"[restore] {args.nemo}", flush=True)
+    model = nemo_asr.models.ASRModel.restore_from(str(args.nemo.expanduser().resolve()), map_location="cpu").eval()
+    model.encoder.change_attention_model(
+        self_attention_model="rel_pos_local_attn" if local_attn else None,
+        att_context_size=att_context,
+        update_config=False,
+        device=torch.device("cpu"),
+    )
+    model.encoder.setup_streaming_params(att_context_size=att_context)
+    if not local_attn:
+        install_static_full_cache_masks(model.encoder, att_context)
+
+    cfg = model.encoder.streaming_cfg
+    pre_encode = int(cfg.pre_encode_cache_size[1] if isinstance(cfg.pre_encode_cache_size, list) else cfg.pre_encode_cache_size)
+    chunk = int(cfg.chunk_size[1] if isinstance(cfg.chunk_size, list) else cfg.chunk_size)
+    shift = int(cfg.shift_size[1] if isinstance(cfg.shift_size, list) else cfg.shift_size)
+    feature_frames = pre_encode + chunk  # left-context cache frames + streaming chunk
+    constant_cache_len = int(cfg.last_channel_cache_size)
+    valid_out_len = int(cfg.valid_out_len)
+
+    step = StreamingCTCStep(model, att_context, feature_frames, constant_cache_len, local_attn=local_attn).eval()
+    cache_channel, cache_time, _cache_len = model.encoder.get_initial_cache_state(1, torch.float32, torch.device("cpu"))
+    x = torch.randn(1, 80, feature_frames, dtype=torch.float32)
+    with torch.no_grad():
+        logits, next_channel, next_time = step(x, cache_channel, cache_time)
+    print(
+        f"[probe] att={att_context} pre_encode={pre_encode} chunk={chunk} shift={shift} "
+        f"feature_frames={feature_frames} valid_out_len={valid_out_len} logits={tuple(logits.shape)} "
+        f"cache_channel={tuple(cache_channel.shape)} cache_time={tuple(cache_time.shape)}",
+        flush=True,
+    )
+
+    ts_path = out_dir / f"{args.name}.torchscript.pt"
+    print(f"[trace] {ts_path}", flush=True)
+    with torch.no_grad():
+        traced = torch.jit.trace(step, (x, cache_channel, cache_time), strict=False, check_trace=False).eval()
+        traced.save(str(ts_path))
+
+    fp32_path = out_dir / f"{args.name.replace('_fp16', '_fp32')}.mlmodel"
+    fp16_path = out_dir / f"{args.name}.mlmodel"
+    for p in [fp32_path, fp16_path]:
+        if p.exists():
+            p.unlink()
+    print(f"[convert] neuralnetwork iOS14-target fp32 -> {fp32_path}", flush=True)
+    mlmodel = ct.convert(
+        traced,
+        source="pytorch",
+        convert_to="neuralnetwork",
+        minimum_deployment_target=ct.target.iOS14,
+        inputs=[
+            ct.TensorType(name="processed_signal", shape=x.shape, dtype=np.float32),
+            ct.TensorType(name="cache_last_channel", shape=cache_channel.shape, dtype=np.float32),
+            ct.TensorType(name="cache_last_time", shape=cache_time.shape, dtype=np.float32),
+        ],
+        outputs=[
+            ct.TensorType(name="logits"),
+            ct.TensorType(name="cache_last_channel_next"),
+            ct.TensorType(name="cache_last_time_next"),
+        ],
+    )
+    mlmodel.save(str(fp32_path))
+
+    print(f"[quantize] fp16 weights -> {fp16_path}", flush=True)
+    fp16_model = quantization_utils.quantize_weights(mlmodel, nbits=16)
+    fp16_model.save(str(fp16_path))
+    if not args.keep_fp32 and fp32_path.exists():
+        fp32_path.unlink()
+
+    smoke = ct.models.MLModel(str(fp16_path))
+    pred = smoke.predict({
+        "processed_signal": x.numpy().astype(np.float32),
+        "cache_last_channel": cache_channel.numpy().astype(np.float32),
+        "cache_last_time": cache_time.numpy().astype(np.float32),
+    })
+    pred_shapes = {k: list(np.asarray(v).shape) for k, v in pred.items()}
+    # argmax agreement of the CoreML fp16 step vs the torch fp32 step on this input
+    torch_arg = logits.detach().numpy().reshape(-1, logits.shape[-1]).argmax(-1)
+    cm_logits = np.asarray(pred["logits"]).reshape(-1, logits.shape[-1])
+    cm_arg = cm_logits.argmax(-1)
+    n = min(len(torch_arg), len(cm_arg))
+    agree = float((torch_arg[:n] == cm_arg[:n]).mean()) if n else 0.0
+
+    manifest = {
+        "created_at_utc": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+        "source_repo": "Reza2kn/Shenava-Koochik-1.0",
+        "source_nemo": str(args.nemo.expanduser().resolve()),
+        "format": "CoreML NeuralNetwork iOS14-target fp16-weight true cache-aware streaming CTC step",
+        "att_context": att_context,
+        "self_attention_model": "rel_pos_local_attn" if local_attn else "static_full_cache_mask",
+        "pre_encode_cache_size": pre_encode,
+        "chunk_size": chunk,
+        "shift_size": shift,
+        "feature_frames": feature_frames,
+        "audio_ms_per_prediction": feature_frames * 10,
+        "valid_out_len": valid_out_len,
+        "constant_cache_len": constant_cache_len,
+        "vocab_size": int(logits.shape[-1]),
+        "inputs": {
+            "processed_signal": list(x.shape),
+            "cache_last_channel": list(cache_channel.shape),
+            "cache_last_time": list(cache_time.shape),
+        },
+        "outputs": {
+            "logits": list(logits.shape),
+            "cache_last_channel_next": list(next_channel.shape),
+            "cache_last_time_next": list(next_time.shape),
+        },
+        "coreml_predict_shapes": pred_shapes,
+        "fp16_vs_fp32_argmax_agreement": agree,
+        "artifacts": {"mlmodel": str(fp16_path), "bytes": package_size(fp16_path)},
+    }
+    (out_dir / f"{args.name}_manifest.json").write_text(json.dumps(manifest, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
+    print(f"[done] {args.name} | feature_frames={feature_frames} valid_out={valid_out_len} "
+          f"argmax_agree={agree:.4f} bytes={package_size(fp16_path)}", flush=True)
+
+
+if __name__ == "__main__":
+    main()

mel_filters_slaney_80x257.json

@@ -0,0 +1 @@
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+    "نی",
+    "ها",
+    "▁سر",
+    "ایی",
+    "انی",
+    "▁خی",
+    "له",
+    "جا",
+    "▁ل",
+    "ره",
+    "▁چه",
+    "خت",
+    "ات",
+    "اید",
+    "کن",
+    "رم",
+    "▁ام",
+    "اق",
+    "▁مو",
+    "گر",
+    "اری",
+    "▁نه",
+    "از",
+    "▁ط",
+    "اره",
+    "▁خیلی",
+    "عد",
+    "▁دست",
+    "▁ال",
+    "▁ان",
+    "اس",
+    "اده",
+    "▁پی",
+    "▁هر",
+    "شم",
+    "▁حال",
+    "ول",
+    "در",
+    "رف",
+    "وم",
+    "▁داشت",
+    "بی",
+    "▁شما",
+    "▁دیگه",
+    "انه",
+    "▁بد",
+    "ونه",
+    "گی",
+    "▁هست",
+    "▁بعد",
+    "▁ند",
+    "▁گر",
+    "▁همه",
+    "▁رفت",
+    "وری",
+    "مد",
+    "▁شده",
+    "اش",
+    "▁نیست",
+    "گاه",
+    "که",
+    "▁غ",
+    "▁بگ",
+    "▁داد",
+    "▁کنم",
+    "است",
+    "مان",
+    "کر",
+    "شون",
+    "▁باید",
+    "▁مث",
+    "▁تر",
+    "▁وق",
+    "▁خب",
+    "▁یا",
+    "قی",
+    "دم",
+    "دا",
+    "▁ولی",
+    "دی",
+    "خو",
+    "بت",
+    "▁اس",
+    "▁فر",
+    "▁بب",
+    "شن",
+    "▁مع",
+    "▁پر",
+    "▁مح",
+    "▁پس",
+    "▁هی",
+    "▁سال",
+    "وش",
+    "▁بز",
+    "▁شه",
+    "▁کم",
+    "▁مرد",
+    "های",
+    "چه",
+    "فر",
+    "عی",
+    "▁اما",
+    "یده",
+    "وز",
+    "▁سی",
+    "▁همین",
+    "▁باز",
+    "▁روز",
+    "کی",
+    "▁ات",
+    "تون",
+    "▁اص",
+    "▁نب",
+    "▁باش",
+    "هم",
+    "▁کش",
+    "▁مر",
+    "▁آق",
+    "▁گرفت",
+    "به",
+    "▁دل",
+    "▁توی",
+    "▁روی",
+    "▁رس",
+    "نده",
+    "وان",
+    "▁قر",
+    "▁نش",
+    "▁سا",
+    "▁داره",
+    "▁خواه",
+    "یا",
+    "نج",
+    "▁حالا",
+    "▁بین",
+    "زار",
+    "کت",
+    "▁نظ",
+    "انم",
+    "▁کردن",
+    "▁کنه",
+    "▁هیچ",
+    "▁مت",
+    "▁راه",
+    "▁کرده",
+    "▁دوست",
+    "▁ده",
+    "با",
+    "▁فکر",
+    "▁حرف",
+    "زه",
+    "ادی",
+    "عت",
+    "▁پیش",
+    "امه",
+    "▁آم",
+    "▁مس",
+    "▁چند",
+    "▁دید",
+    "▁گذ",
+    "▁یکی",
+    "▁یع",
+    "▁چون",
+    "الی",
+    "▁یعنی",
+    "▁کو",
+    "▁زند",
+    "▁کردم",
+    "▁باشه",
+    "▁ببین",
+    "▁اند",
+    "جه",
+    "▁اینجا",
+    "لو",
+    "اند",
+    "▁خا",
+    "▁صد",
+    "مین",
+    "اف",
+    "شک",
+    "ونی",
+    "▁اینکه",
+    "سته",
+    "▁تم",
+    "▁چرا",
+    "▁زی",
+    "▁کند",
+    "▁واق",
+    "▁کی",
+    "▁نو",
+    "رده",
+    "▁وقتی",
+    "▁ایر",
+    "▁اح",
+    "▁عم",
+    "نه",
+    "ادر",
+    "▁شن",
+    "بر",
+    "▁دور",
+    "قط",
+    "لام",
+    "ق��",
+    "▁ار",
+    "▁بخ",
+    "ونم",
+    "سه",
+    "▁کنیم",
+    "▁چیزی",
+    "▁بار",
+    "▁اگر",
+    "عه",
+    "▁سو",
+    "▁جم",
+    "▁پای",
+    "لم",
+    "▁زد",
+    "شی",
+    "▁اول",
+    "▁اگه",
+    "▁حس",
+    "رگ",
+    "▁مثلا",
+    "▁بچه",
+    "▁قب",
+    "▁میشه",
+    "▁اصلا",
+    "▁دارم",
+    "▁اینا",
+    "▁مد",
+    "▁الان",
+    "▁فقط",
+    "ارد",
+    "▁شک",
+    "▁بل",
+    "▁کنی",
+    "مت",
+    "▁خودش",
+    "▁چشم",
+    "▁شر",
+    "▁مق",
+    "▁کسی",
+    "▁ری",
+    "ضی",
+    "▁خدا",
+    "▁چیز",
+    "▁آب",
+    "ارم",
+    "▁نم",
+    "▁بیشت",
+    "صد",
+    "وه",
+    "کنه",
+    "باره",
+    "عا",
+    "▁زن",
+    "▁مه",
+    "▁افت",
+    "فا",
+    "طر",
+    "▁پنج",
+    "فی",
+    "وند",
+    "▁نا",
+    "▁یاد",
+    "▁کت",
+    "▁نگاه",
+    "▁تن",
+    "▁مثل",
+    "▁نبود",
+    "▁ایران",
+    "▁خوب",
+    "▁انگ",
+    "▁هزار",
+    "▁جان",
+    "▁مج",
+    "▁میگ",
+    "▁برد",
+    "ورد",
+    "▁جو",
+    "▁سه",
+    "▁وقت",
+    "▁آخ",
+    "▁زندگی",
+    "یری",
+    "وا",
+    "▁بالا",
+    "قدر",
+    "وت",
+    "جود",
+    "مون",
+    "▁خوش",
+    "▁نظر",
+    "▁شب",
+    "▁شود",
+    "صی",
+    "▁خواست",
+    "شته",
+    "شان",
+    "▁بودن",
+    "▁کنید",
+    "▁هن",
+    "▁دارد",
+    "▁بیشتر",
+    "▁گو",
+    "▁آقای",
+    "▁جنگ",
+    "▁دان",
+    "▁دیگر",
+    "▁بزرگ",
+    "▁اش",
+    "تش",
+    "▁آقا",
+    "▁آدم",
+    "▁بیر",
+    "▁مید",
+    "اهی",
+    "اک",
+    "▁گفتم",
+    "▁اومد",
+    "▁درست",
+    "▁تح",
+    "▁پید",
+    "▁کتاب",
+    "▁بده",
+    "ایت",
+    "▁نز",
+    "▁جه",
+    "جی",
+    "یدم",
+    "▁اد",
+    "▁مرا",
+    "▁بودم",
+    "▁صح",
+    "بان",
+    "▁بله",
+    "▁شم",
+    "یره",
+    "شین",
+    "▁کجا",
+    "من",
+    "کرد",
+    "▁برگ",
+    "▁زمین",
+    "▁بیرون",
+    "▁آمد",
+    "▁خونه",
+    "▁زیر",
+    "▁آنها",
+    "▁مردم",
+    "زم",
+    "▁همون",
+    "ستان",
+    "فته",
+    "▁نق",
+    "اخ",
+    "▁تمام",
+    "▁تص",
+    "یدی",
+    "▁شهر",
+    "▁انج",
+    "قت",
+    "▁وجود",
+    "سم",
+    "▁گرد",
+    "▁لب",
+    "▁جای",
+    "▁مش",
+    "▁تع",
+    "ستم",
+    "کس",
+    "▁ذ",
+    "▁آره",
+    "▁خانم",
+    "کار",
+    "طور",
+    "▁بن",
+    "▁خر",
+    "▁پدر",
+    "▁بسی",
+    "▁کاری",
+    "▁شدن",
+    "▁قرار",
+    "▁خودم",
+    "▁پیدا",
+    "▁مادر",
+    "یشه",
+    "وس",
+    "فاق",
+    "▁داشته",
+    "▁داری",
+    "▁واقعا",
+    "شو",
+    "بال",
+    "▁اف",
+    "▁نام",
+    "لت",
+    "اخت",
+    "▁طرف",
+    "▁میخو",
+    "▁جن",
+    "یدن",
+    "ورت",
+    "▁کنن",
+    "▁ض",
+    "ارت",
+    "اح",
+    "▁دخ",
+    "فه",
+    "▁نداشت",
+    "▁انت",
+    "▁بهتر",
+    "▁اتفاق",
+    "▁بازی",
+    "▁مهم",
+    "▁ست",
+    "▁کنند",
+    "▁کل",
+    "▁شاید",
+    "▁بیا",
+    "▁علی",
+    "▁کام",
+    "▁دنی",
+    "▁بوده",
+    "▁انجام",
+    "▁بشه",
+    "▁شاه",
+    "▁پشت",
+    "ینه",
+    "▁آر",
+    "جر",
+    "▁باشد",
+    "ریک",
+    "▁جا",
+    "▁بودند",
+    "▁توان",
+    "▁حتی",
+    "ویی",
+    "▁خان",
+    "▁شرو",
+    "▁صدای",
+    "▁بهش",
+    "▁دختر",
+    "▁هنوز",
+    "▁مخ",
+    "تم",
+    "▁شروع",
+    "نامه",
+    "▁کنار",
+    "▁نگ",
+    "وب",
+    "▁تق",
+    "مو",
+    "▁وی",
+    "کان",
+    "▁گذاشت",
+    "▁اتاق",
+    "▁کردند",
+    "▁خواب",
+    "ظه",
+    "▁لا",
+    "▁هایی",
+    "لف",
+    "▁مط",
+    "▁چهار",
+    "▁داریم",
+    "▁میکن",
+    "▁اب",
+    "▁آیا",
+    "▁فرم",
+    "▁خانه",
+    "▁میز",
+    "بار",
+    "▁تون",
+    "خی",
+    "امی",
+    "▁موق",
+    "▁پول",
+    "▁بگیر",
+    "ینی",
+    "▁کس",
+    "▁کشور",
+    "▁جل",
+    "▁پسر",
+    "▁اط",
+    "▁خون",
+    "▁آورد",
+    "▁صحبت",
+    "▁همچ",
+    "نین",
+    "▁پیر",
+    "▁فی",
+    "گان",
+    "▁تاری",
+    "▁بلند",
+    "ستی",
+    "شید",
+    "بته",
+    "▁رسید",
+    "▁برو",
+    "نم",
+    "▁گو��",
+    "▁فرو",
+    "▁دن",
+    "▁نفر",
+    "▁بابا",
+    "▁گل",
+    "▁البته",
+    "▁نف",
+    "▁شو",
+    "ایه",
+    "یه",
+    "▁حا",
+    "▁آخر",
+    "ضا",
+    "▁کمک",
+    "▁خورد",
+    "روز",
+    "▁ماه",
+    "ذار",
+    "▁خاطر",
+    "▁مورد",
+    "▁ته",
+    "▁حق",
+    "▁زمان",
+    "▁ساخت",
+    "▁همیشه",
+    "▁لط",
+    "▁مم",
+    "▁بسیار",
+    "▁بکن",
+    "▁سپ",
+    "▁ساعت",
+    "رب",
+    "▁آه",
+    "مه",
+    "▁بخو",
+    "دید",
+    "▁شی",
+    "▁نزدی",
+    "▁مشک",
+    "کتر",
+    "▁اونجا",
+    "رات",
+    "▁جز",
+    "اسی",
+    "▁قبل",
+    "▁پرو",
+    "شد",
+    "▁قدر",
+    "▁هفت",
+    "▁دوباره",
+    "▁خبر",
+    "یت",
+    "▁ور",
+    "طوری",
+    "▁نس",
+    "▁حم",
+    "ازه",
+    "▁حد",
+    "▁دقی",
+    "فاده",
+    "▁اسم",
+    "▁دنبال",
+    "▁منو",
+    "▁بگو",
+    "▁زود",
+    "▁اع",
+    "▁اخ",
+    "▁سلام",
+    "▁درد",
+    "▁اینه",
+    "▁شدم",
+    "▁اه",
+    "سان",
+    "▁سخ",
+    "اط",
+    "▁افتاد",
+    "ایش",
+    "▁امروز",
+    "▁استفاده",
+    "▁درباره",
+    "تما",
+    "▁خور",
+    "▁داده",
+    "▁صب",
+    "نان",
+    "▁شیر",
+    "▁مام",
+    "▁بک",
+    "▁کوچ",
+    "▁خودت",
+    "▁پرس",
+    "ندی",
+    "▁کردیم",
+    "اپ",
+    "▁صورت",
+    "▁سری",
+    "▁لح",
+    "لب",
+    "▁تنها",
+    "عیت",
+    "▁دارن",
+    "▁عق",
+    "▁دنیا",
+    "▁هشت",
+    "▁سنگ",
+    "▁چو",
+    "▁حر",
+    "▁تب",
+    "▁سف",
+    "رت",
+    "▁بیم",
+    "▁چیه",
+    "اله",
+    "جوری",
+    "▁میر",
+    "▁مست",
+    "▁فرد",
+    "▁نداره",
+    "▁ساز",
+    "▁کردی",
+    "▁بع",
+    "ابی",
+    "▁مان",
+    "لیس",
+    "▁عش",
+    "دار",
+    "▁آمریک",
+    "▁عن",
+    "▁خوبی",
+    "▁گرفته",
+    "▁اج",
+    "▁بیست",
+    "▁میان",
+    "▁بدون",
+    "▁ث",
+    "یش",
+    "▁فهم",
+    "▁واس",
+    "نت",
+    "▁بریم",
+    "▁احس",
+    "▁صبح",
+    "توان",
+    "▁وا",
+    "▁حک",
+    "▁منم",
+    "وق",
+    "▁داست",
+    "▁خط",
+    "صه",
+    "▁موقع",
+    "غی",
+    "وع",
+    "▁وارد",
+    "▁کد",
+    "▁قط",
+    "▁تش",
+    "▁دانش",
+    "سط",
+    "▁اعت",
+    "▁تک",
+    "▁منت",
+    "▁نزدیک",
+    "▁لی",
+    "▁برم",
+    "▁زیاد",
+    "حت",
+    "▁مص",
+    "▁کمی",
+    "▁رفته",
+    "▁قد",
+    "ران",
+    "▁نکن",
+    "▁نیر",
+    "▁همان",
+    "مانی",
+    "▁دیو",
+    "▁میکنه",
+    "▁چقدر",
+    "▁ایم",
+    "▁دون",
+    "▁میک",
+    "▁پا",
+    "نش",
+    "▁ماشین",
+    "▁خد",
+    "▁سمت",
+    "▁راست",
+    "▁جلو",
+    "▁بس",
+    "▁مدر",
+    "ایم",
+    "▁خار",
+    "گری",
+    "▁جهان",
+    "شتی",
+    "ابل",
+    "لوم",
+    "▁گیر",
+    "▁خواهد",
+    "▁احساس",
+    "▁عب",
+    "▁جواب",
+    "▁آد",
+    "یس",
+    "میم",
+    "▁پایین",
+    "▁نگر",
+    "▁هستم",
+    "▁دکتر",
+    "▁بف",
+    "▁مثلاً",
+    "ایل",
+    "▁صدا",
+    "▁بند",
+    "▁سل",
+    "▁تی",
+    "لات",
+    "▁نک",
+    "▁آز",
+    "خته",
+    "ودی",
+    "یند",
+    "▁بال",
+    "▁اونا",
+    "قا",
+    "▁انگار",
+    "▁جمع",
+    "▁ره",
+    "▁جام",
+    "▁جایی",
+    "▁نیز",
+    "سر",
+    "▁میاد",
+    "▁داستان",
+    "▁گرو",
+    "صل",
+    "تا",
+    "▁عشق",
+    "▁اینو",
+    "▁بگم",
+    "▁ظ",
+    "▁دیدم",
+    "▁مون",
+    "▁کلا",
+    "▁دیده",
+    "▁رنگ",
+    "▁تازه",
+    "▁گی",
+    "▁میده",
+    "▁وای",
+    "▁لطفا",
+    "صو",
+    "▁ژ",
+    "▁هستند",
+    "▁کشید",
+    "▁غذ",
+    "▁حض",
+    "▁برنامه",
+    "▁دلی",
+    "▁رفتن",
+    "▁پاد",
+    "▁زیادی",
+    "زش",
+    "▁شرکت",
+    "▁خوام",
+    "▁سب",
+    "▁ترس",
+    "▁دونم",
+    "▁خواهم",
+    "جب",
+    "▁غیر",
+    "الم",
+    "▁بزن",
+    "ترین",
+    "خره",
+    "▁عنوان",
+    "▁آل",
+    "▁گم",
+    "▁ببینم",
+    "▁عزی",
+    "▁بری",
+    "ریف",
+    "▁دم",
+    "▁بپ",
+    "تو",
+    "▁امید",
+    "▁طول",
+    "▁میگه",
+    "▁دادن",
+    "▁افر",
+    "▁ادامه",
+    "▁واسه",
+    "▁موض",
+    "طی",
+    "▁نگه",
+    "قد",
+    "▁خاک",
+    "▁مال",
+    "ژه",
+    "▁داخ",
+    "▁نیاز",
+    "▁بش",
+    "▁خانو",
+    "▁چطور",
+    "نا",
+    "▁",
+    "ا",
+    "ی",
+    "ر",
+    "ن",
+    "ه",
+    "م",
+    "د",
+    "و",
+    "ب",
+    "ت",
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