Upload OmniVoice LoRA checkpoint-200 for arabic
Browse files- .gitattributes +1 -0
- README.md +56 -0
- chat_template.jinja +89 -0
- config.json +101 -0
- model.safetensors +3 -0
- optimizer.bin +3 -0
- random_states_0.pkl +3 -0
- scheduler.bin +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +23 -0
- train_config.json +53 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -0,0 +1,56 @@
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---
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language:
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- ar
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license: apache-2.0
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tags:
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- omnivoice
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- voice-cloning
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- lora
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- speech-synthesis
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- tts
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base_model: k2-fsa/OmniVoice
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library_name: peft
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---
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# OmniVoice LoRA — Arabic (ar)
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Fine-tuned LoRA adapter for [OmniVoice](https://huggingface.co/k2-fsa/OmniVoice) to improve zero-shot voice cloning quality for **Arabic**.
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## Training Details
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- **Base model:** k2-fsa/OmniVoice (Qwen3-0.6B backbone)
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- **Method:** LoRA (rank=32, alpha=64, RSLoRA)
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- **Target modules:** Self-attention + audio projection layers
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- **Training data:** Best-of-N distilled Arabic speech samples
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- **Steps:** 200
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- **Precision:** bf16
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- **Hardware:** NVIDIA A40 (48GB)
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## Usage
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```python
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from omnivoice import OmniVoice
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from peft import PeftModel
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import torch
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# Load base model
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model = OmniVoice.from_pretrained(
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"k2-fsa/OmniVoice",
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device_map="cuda:0",
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dtype=torch.float16,
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)
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# Load LoRA adapter
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model.llm = PeftModel.from_pretrained(model.llm, "amanuelbyte/omnivoice-lora-ar")
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model.llm = model.llm.merge_and_unload()
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# Generate
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audio = model.generate(
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text="Your arabic text here",
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ref_audio="path/to/reference.wav",
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)
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```
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## IWSLT 2026
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This adapter was developed for the IWSLT 2026 shared task on cross-lingual voice cloning.
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# 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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- if enable_thinking is defined and enable_thinking is false %}
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{{- '<think>\n\n</think>\n\n' }}
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{%- endif %}
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{%- endif %}
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config.json
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{
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| 2 |
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"architectures": [
|
| 3 |
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"OmniVoice"
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| 4 |
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],
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| 5 |
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"audio_codebook_weights": [
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| 6 |
+
8,
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| 7 |
+
8,
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| 8 |
+
6,
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| 9 |
+
6,
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| 10 |
+
4,
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| 11 |
+
4,
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| 12 |
+
2,
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| 13 |
+
2
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| 14 |
+
],
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| 15 |
+
"audio_mask_id": 1024,
|
| 16 |
+
"audio_vocab_size": 1025,
|
| 17 |
+
"bos_token_id": null,
|
| 18 |
+
"dtype": "float32",
|
| 19 |
+
"eos_token_id": 151645,
|
| 20 |
+
"llm_config": {
|
| 21 |
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"_name_or_path": "",
|
| 22 |
+
"architectures": [
|
| 23 |
+
"Qwen3ForCausalLM"
|
| 24 |
+
],
|
| 25 |
+
"attention_bias": false,
|
| 26 |
+
"attention_dropout": 0.0,
|
| 27 |
+
"bos_token_id": 151643,
|
| 28 |
+
"chunk_size_feed_forward": 0,
|
| 29 |
+
"dtype": "float32",
|
| 30 |
+
"eos_token_id": 151645,
|
| 31 |
+
"head_dim": 128,
|
| 32 |
+
"hidden_act": "silu",
|
| 33 |
+
"hidden_size": 1024,
|
| 34 |
+
"id2label": {
|
| 35 |
+
"0": "LABEL_0",
|
| 36 |
+
"1": "LABEL_1"
|
| 37 |
+
},
|
| 38 |
+
"initializer_range": 0.02,
|
| 39 |
+
"intermediate_size": 3072,
|
| 40 |
+
"is_encoder_decoder": false,
|
| 41 |
+
"label2id": {
|
| 42 |
+
"LABEL_0": 0,
|
| 43 |
+
"LABEL_1": 1
|
| 44 |
+
},
|
| 45 |
+
"layer_types": [
|
| 46 |
+
"full_attention",
|
| 47 |
+
"full_attention",
|
| 48 |
+
"full_attention",
|
| 49 |
+
"full_attention",
|
| 50 |
+
"full_attention",
|
| 51 |
+
"full_attention",
|
| 52 |
+
"full_attention",
|
| 53 |
+
"full_attention",
|
| 54 |
+
"full_attention",
|
| 55 |
+
"full_attention",
|
| 56 |
+
"full_attention",
|
| 57 |
+
"full_attention",
|
| 58 |
+
"full_attention",
|
| 59 |
+
"full_attention",
|
| 60 |
+
"full_attention",
|
| 61 |
+
"full_attention",
|
| 62 |
+
"full_attention",
|
| 63 |
+
"full_attention",
|
| 64 |
+
"full_attention",
|
| 65 |
+
"full_attention",
|
| 66 |
+
"full_attention",
|
| 67 |
+
"full_attention",
|
| 68 |
+
"full_attention",
|
| 69 |
+
"full_attention",
|
| 70 |
+
"full_attention",
|
| 71 |
+
"full_attention",
|
| 72 |
+
"full_attention",
|
| 73 |
+
"full_attention"
|
| 74 |
+
],
|
| 75 |
+
"max_position_embeddings": 40960,
|
| 76 |
+
"max_window_layers": 28,
|
| 77 |
+
"model_type": "qwen3",
|
| 78 |
+
"num_attention_heads": 16,
|
| 79 |
+
"num_hidden_layers": 28,
|
| 80 |
+
"num_key_value_heads": 8,
|
| 81 |
+
"output_attentions": false,
|
| 82 |
+
"output_hidden_states": false,
|
| 83 |
+
"pad_token_id": null,
|
| 84 |
+
"problem_type": null,
|
| 85 |
+
"return_dict": true,
|
| 86 |
+
"rms_norm_eps": 1e-06,
|
| 87 |
+
"rope_parameters": {
|
| 88 |
+
"rope_theta": 1000000,
|
| 89 |
+
"rope_type": "default"
|
| 90 |
+
},
|
| 91 |
+
"sliding_window": null,
|
| 92 |
+
"tie_word_embeddings": true,
|
| 93 |
+
"use_cache": false,
|
| 94 |
+
"use_sliding_window": false,
|
| 95 |
+
"vocab_size": 151676
|
| 96 |
+
},
|
| 97 |
+
"model_type": "omnivoice",
|
| 98 |
+
"num_audio_codebook": 8,
|
| 99 |
+
"pad_token_id": 151643,
|
| 100 |
+
"transformers_version": "5.5.4"
|
| 101 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
| 1 |
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version https://git-lfs.github.com/spec/v1
|
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optimizer.bin
ADDED
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| 1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:6b4b47651554111a1092b884c6d177a7bcc911aa4c2799ee32433f2b1c0231b4
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size 296162369
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random_states_0.pkl
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:37775e7998c4e2b4deea45da06e47d368c4cc866ee1e4db3a097a4bf144d11f6
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size 14821
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scheduler.bin
ADDED
|
@@ -0,0 +1,3 @@
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|
| 1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:852ddef988f7103509d70cf54769a5ed7d2b40d1db1b9f7ee860bc8add329b23
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size 1401
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tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:408f669b7e2b045fdf54201d815bd364e6667dbd845115da81239c40bc6dcfd1
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size 11423986
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tokenizer_config.json
ADDED
|
@@ -0,0 +1,23 @@
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|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
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"backend": "tokenizers",
|
| 4 |
+
"bos_token": null,
|
| 5 |
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"clean_up_tokenization_spaces": false,
|
| 6 |
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"eos_token": "<|im_end|>",
|
| 7 |
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"errors": "replace",
|
| 8 |
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"extra_special_tokens": [
|
| 9 |
+
"<|denoise|>",
|
| 10 |
+
"<|lang_start|>",
|
| 11 |
+
"<|lang_end|>",
|
| 12 |
+
"<|instruct_start|>",
|
| 13 |
+
"<|instruct_end|>",
|
| 14 |
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"<|text_start|>",
|
| 15 |
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"<|text_end|>"
|
| 16 |
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],
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| 17 |
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"is_local": false,
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| 18 |
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|
| 19 |
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"pad_token": "<|endoftext|>",
|
| 20 |
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"split_special_tokens": false,
|
| 21 |
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"tokenizer_class": "Qwen2Tokenizer",
|
| 22 |
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"unk_token": null
|
| 23 |
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}
|
train_config.json
ADDED
|
@@ -0,0 +1,53 @@
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|
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|
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|
|
|
|
|
|
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|
|
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|
|
| 1 |
+
{
|
| 2 |
+
"output_dir": "./exp/omnivoice_finetuned_ar",
|
| 3 |
+
"data_config": "./data/finetune_ar/config/data_config.json",
|
| 4 |
+
"llm_name_or_path": "Qwen/Qwen3-0.6B",
|
| 5 |
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"audio_vocab_size": 1025,
|
| 6 |
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"audio_mask_id": 1024,
|
| 7 |
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"num_audio_codebook": 8,
|
| 8 |
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"audio_codebook_weights": [
|
| 9 |
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8,
|
| 10 |
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8,
|
| 11 |
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6,
|
| 12 |
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|
| 13 |
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4,
|
| 14 |
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4,
|
| 15 |
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2,
|
| 16 |
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2
|
| 17 |
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],
|
| 18 |
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"drop_cond_ratio": 0.05,
|
| 19 |
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"prompt_ratio_range": [
|
| 20 |
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0.3,
|
| 21 |
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0.7
|
| 22 |
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],
|
| 23 |
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"mask_ratio_range": [
|
| 24 |
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0.0,
|
| 25 |
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1.0
|
| 26 |
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],
|
| 27 |
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"language_ratio": 1.0,
|
| 28 |
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"use_pinyin_ratio": 0.0,
|
| 29 |
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"instruct_ratio": 0.0,
|
| 30 |
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"only_instruct_ratio": 0.0,
|
| 31 |
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"resume_from_checkpoint": null,
|
| 32 |
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"init_from_checkpoint": "k2-fsa/OmniVoice",
|
| 33 |
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"learning_rate": 0.0001,
|
| 34 |
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"weight_decay": 0.01,
|
| 35 |
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"max_grad_norm": 1.0,
|
| 36 |
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"steps": 400,
|
| 37 |
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"seed": 42,
|
| 38 |
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"lr_scheduler_type": "cosine",
|
| 39 |
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"warmup_type": "ratio",
|
| 40 |
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"warmup_ratio": 0.05,
|
| 41 |
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"warmup_steps": 2000,
|
| 42 |
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"batch_tokens": 8192,
|
| 43 |
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"gradient_accumulation_steps": 8,
|
| 44 |
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"num_workers": 4,
|
| 45 |
+
"mixed_precision": "bf16",
|
| 46 |
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"allow_tf32": true,
|
| 47 |
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"use_deepspeed": false,
|
| 48 |
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"deepspeed_config": null,
|
| 49 |
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"logging_steps": 10,
|
| 50 |
+
"eval_steps": 100,
|
| 51 |
+
"save_steps": 100,
|
| 52 |
+
"keep_last_n_checkpoints": 3
|
| 53 |
+
}
|