first commit

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README.md

@@ -1,3 +1,59 @@
----
-license: mit
----
+---
+license: mit
+language:
+- en
+- zh
+base_model:
+- VoxCPM
+pipeline_tag: text-to-speech
+library_name: transformers
+tags:
+- VoxCPM
+- Speech
+---
+
+# VoxCPM  
+This version of VoxCPM has been converted to run on the Axera NPU using **w8a16** quantization.
+Compatible with Pulsar2 version: 4.2
+
+## Convert tools links:
+For those who are interested in model conversion, you can try to export axmodel through the original repo : 
+[VoxCPM offical](https://github.com/OpenBMB/VoxCPM/)
+
+[Pulsar2 Link, How to Convert LLM from Huggingface to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/appendix/build_llm.html) 
+
+[AXera NPU HOST LLM Runtime](https://github.com/AXERA-TECH/VoxCPM.Axera) 
+
+## Support Platform
+
+- AX650
+  - AX650N DEMO Board
+  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
+  - [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
+
+
+
+## How to use
+
+Download all files from this repository to the device  
+### 1. Install packages    
+
+#### 1. Install voxcpm axinfer package  
+```
+git clone -b 1.0.4-axmode_infer https://github.com/techshoww/VoxCPM.git 
+cd VoxCPM
+pip3 install .
+```
+
+#### 2. Download zipenhancer
+```
+pip3 install modelscope  
+modelscope download --model iic/speech_zipenhancer_ans_multiloss_16k_base --local_dir iic/speech_zipenhancer_ans_multiloss_16k_base
+```
+
+### 2. Run on Axera Device    
+Go to the root directory of this project.  run:  
+```
+python3 run_ax650.py
+```
+

VoxCPM-0.5B/config.json

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+{
+    "architecture": "voxcpm",
+    "lm_config": {
+        "bos_token_id": 1,
+        "eos_token_id": 2,
+        "hidden_size": 1024,
+        "intermediate_size": 4096,
+        "max_position_embeddings": 32768,
+        "num_attention_heads": 16,
+        "num_hidden_layers": 24,
+        "num_key_value_heads": 2,
+        "rms_norm_eps": 1e-05,
+        "rope_theta": 10000,
+        "rope_scaling": {
+            "type": "longrope", 
+            "long_factor": [1.0004360675811768, 1.0668443441390991, 1.1631425619125366, 1.3025742769241333, 1.5040205717086792, 1.7941505908966064, 2.2101221084594727, 2.802666664123535, 3.6389970779418945, 4.804192543029785, 6.39855432510376, 8.527148246765137, 11.277542114257812, 14.684998512268066, 18.69317054748535, 23.13019371032715, 27.72362518310547, 32.1606559753418, 36.168827056884766, 39.57627868652344, 42.32667541503906, 44.45526885986328, 46.04962921142578, 47.21482849121094, 48.05115509033203, 48.64370346069336, 49.05967712402344, 49.34980392456055, 49.551246643066406, 49.69068145751953, 49.78697967529297, 49.85338592529297],
+            "short_factor": [1.0004360675811768, 1.0668443441390991, 1.1631425619125366, 1.3025742769241333, 1.5040205717086792, 1.7941505908966064, 2.2101221084594727, 2.802666664123535, 3.6389970779418945, 4.804192543029785, 6.39855432510376, 8.527148246765137, 11.277542114257812, 14.684998512268066, 18.69317054748535, 23.13019371032715, 27.72362518310547, 32.1606559753418, 36.168827056884766, 39.57627868652344, 42.32667541503906, 44.45526885986328, 46.04962921142578, 47.21482849121094, 48.05115509033203, 48.64370346069336, 49.05967712402344, 49.34980392456055, 49.551246643066406, 49.69068145751953, 49.78697967529297, 49.85338592529297],
+            "original_max_position_embeddings": 32768
+        },    
+        "vocab_size": 73448,
+        "scale_emb": 12,
+        "dim_model_base": 256,
+        "scale_depth": 1.4,
+        "use_mup": false
+    },
+    "patch_size": 2,
+    "feat_dim": 64,
+    "scalar_quantization_latent_dim": 256,
+    "scalar_quantization_scale": 9,
+    "residual_lm_num_layers": 6,
+    "encoder_config": {
+        "hidden_dim": 1024,
+        "ffn_dim": 4096,
+        "num_heads": 16,
+        "num_layers": 4
+    },
+    "dit_config": {
+        "hidden_dim": 1024,
+        "ffn_dim": 4096,
+        "num_heads": 16,
+        "num_layers": 4,
+        "cfm_config": {
+            "sigma_min": 1e-06,
+            "solver": "euler",
+            "t_scheduler": "log-norm",
+            "inference_cfg_rate": 2.0
+        }
+    },
+    "max_length": 4096,
+    "device": "cuda",
+    "dtype": "bfloat16"
+}

VoxCPM-0.5B/special_tokens_map.json

@@ -0,0 +1,81 @@
+{
+  "additional_special_tokens": [
+    {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false
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+    {
+      "content": "<|im_start|>",
+      "lstrip": false,
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+      "rstrip": false,
+      "single_word": false
+    },
+    {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false
+    },
+    {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false
+    }
+  ],
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

VoxCPM-0.5B/tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
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+      "lstrip": false,
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+      "special": true
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+      "single_word": false,
+      "special": true
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+      "single_word": false,
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+  "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}"
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