初始化项目，由ModelHub XC社区提供模型

Model: ryota-komatsu/SylReg-LM-7B
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+datasets:
+- ryota-komatsu/SylReg
+language:
+- en
+base_model:
+- Qwen/Qwen2.5-7B
+license: cc-by-nc-sa-4.0
+---
+
+# SylReg-LM 7B
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+![](performance.png)
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+- **Model type:** Qwen2ForCausalLM
+- **Language(s) (NLP):** English
+- **License:** CC BY-NC-SA 4.0
+- **Finetuned from model:** [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B)
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [Code](https://github.com/ryota-komatsu/speaker_disentangled_hubert)
+- **Paper:** [arXiv:2607.04064](https://arxiv.org/abs/2607.04064)
+- **Demo:** [Project page](https://ryota-komatsu.github.io/speaker_disentangled_hubert)
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```sh
+git clone https://github.com/ryota-komatsu/speaker_disentangled_hubert.git
+cd speaker_disentangled_hubert
+
+sudo apt install git-lfs  # for UTMOS
+
+conda create -y -n py310 -c pytorch -c nvidia -c conda-forge python=3.10 pip=24.0 setuptools=81.0.0 faiss-gpu=1.13.2
+conda activate py310
+pip install -r requirements/requirements.txt
+
+sh scripts/setup.sh
+```
+
+```python
+import re
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+from src.flow_matching import FlowMatchingWithBigVGan
+from src.s5hubert import SylRegForSyllableDiscovery
+
+wav_path = "/path/to/wav"
+
+# download pretrained models from hugging face hub
+encoder = SylRegForSyllableDiscovery.from_pretrained("ryota-komatsu/SylReg-Distill", device_map="cuda", dtype="auto")
+decoder = FlowMatchingWithBigVGan.from_pretrained("ryota-komatsu/SylReg-Decoder", device_map="cuda", dtype="auto")
+speechlm = AutoModelForCausalLM.from_pretrained("ryota-komatsu/SylReg-LM-7B", device_map="cuda", dtype="auto")
+tokenizer = AutoTokenizer.from_pretrained("ryota-komatsu/SylReg-LM-7B")
+
+# load a waveform
+waveform, sr = torchaudio.load(wav_path)
+waveform = torchaudio.functional.resample(waveform, sr, 16000)
+
+# encode a waveform into syllabic units
+outputs = encoder(waveform.to(encoder.device))
+units = outputs[0]["units"]  # [3950, 67, ..., 503]
+
+# speech language modeling
+text = "".join(f"<{unit}>" for unit in units)
+input_ids = tokenizer(text, padding=True, return_tensors="pt").input_ids.to(speechlm.device)
+generated_ids = speechlm.generate(input_ids=input_ids, do_sample=True, temperature=0.8)[0]
+units = tokenizer.decode(generated_ids)
+units = torch.tensor([int(unit) for unit in re.findall(r"<(\d+)>", units)], device=decoder.device)
+
+# unit-to-speech synthesis
+generated_speech = decoder(units.unsqueeze(0)).waveform.cpu()
+```
+
+## Training Details
+
+### Training Data
+
+|  | Hours | License | Provider |
+| --- | --- | --- | --- |
+| [LibriSpeech](https://huggingface.co/datasets/openslr/librispeech_asr) | 960 | CC BY 4.0 | V. Panayotov *et al.* |
+| [Libriheavy](https://huggingface.co/datasets/pkufool/libriheavy) | 50,978 | public domain | W. Kang *et al.* |
+| [Emilia-Large](https://huggingface.co/datasets/amphion/Emilia-Dataset) | 4,447 | CC BY 4.0, CC BY-NC 4.0 | H. He *et al.* |
+| [People's Speech (clean, clean_sa)](https://huggingface.co/datasets/MLCommons/peoples_speech) | 5,640 | CC-BY, CC-BY-SA | D. Galvez *et al.* |
+| [VoxPopuli](https://huggingface.co/datasets/facebook/voxpopuli) | 543 | CC0-1.0 | C. Wang *et al.* |
+| [TinyStories](https://huggingface.co/datasets/roneneldan/TinyStories) | 27,810 | cdla-sharing-1.0 | R. Eldan *et al.* |
+| [Cosmopedia-v2](https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus) | 38,986 | odc-by | L. B. Allal *et al.* |
+| Total | 129,364 |  |  |
+
+### Training Hyperparameters
+
+- **Training regime:** bf16 mixed precision
+- **Training steps:** 15k
+- **Batch size:** 2,097,152 (=2<sup>21</sup>) tokens
+- **Optimizer:** AdamW(lr=0.0003, betas=(0.9, 0.95), weight_decay=0.01)
+- **Scheduler:** warmup_stable_decay(num_warmup_steps=100, num_decay_steps=5000, min_lr_ratio=0.1)
+
+## Hardware
+
+32 NVIDIA H100 GPUs
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+```bibtex
+@article{Komatsu_SylReg_2026,
+  author    = {Komatsu, Ryota and Kawakita, Kota and Okamoto, Takuma and Shinozaki, Takahiro},
+  title     = {Speaker-Disentangled Chunk-Wise Regression for Syllabic Tokenization},
+  year      = {2026},
+  volume    = {7},
+  journal   = {IEEE Open Journal of Signal Processing},
+  pages     = {},
+}
+```

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" and not message.tool_calls %}
+        {% generation %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+        {% endgeneration %}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "dtype": "bfloat16",
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 131072,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "pad_token_id": 151643,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.1",
+  "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 159857
+}

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special_tokens_map.json

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+    "<|vision_end|>",
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+}

tokenizer.json

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