Replace .pt model with safetensors format (using Git LFS)

- Remove chordia_v0.0.1-alpha.pt
- Add chordia_v0.0.1-alpha.safetensors (safer format, stored via Git LFS)
- Add conversion script for future use
- Configure Git LFS for safetensors files

Benefits of safetensors:
- More secure (avoids pickle security risks)
- Faster loading speed
- Zero-copy capability
- Better for sharing on Hugging Face

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

.gitattributes

@@ -5,3 +5,4 @@
 *.data filter=lfs diff=lfs merge=lfs -text
 *.pkl filter=lfs diff=lfs merge=lfs -text
 *.joblib filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text

chordia_v0.0.1-alpha.pt → chordia_v0.0.1-alpha.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5eade0a9d175177cb5d5e4c1c4d8f470c045968527a211b06368c7e55a092ddf
-size 695562
+oid sha256:a7a6d014049ebb2e80bfa97485370187a734a383e80b3805588abc3bd0415673
+size 675556

convert_to_safetensors.py

@@ -0,0 +1,98 @@
+"""
+将 PyTorch 模型转换为 safetensors 格式
+
+safetensors 优势：
+- 更安全（避免 pickle 安全风险）
+- 加载速度更快
+- 支持零拷贝
+- 更适合在 Hugging Face 等平台共享
+"""
+
+from safetensors.torch import save_file
+import torch
+import os
+from pathlib import Path
+
+
+def convert_to_safetensors(
+    input_path: str,
+    output_path: str = None,
+    metadata: dict = None
+):
+    """
+    将 PyTorch 模型转换为 safetensors 格式
+
+    Args:
+        input_path: 输入的 .pt 或 .pth 文件路径
+        output_path: 输出的 .safetensors 文件路径（可选）
+        metadata: 要保存的元数据（可选）
+    """
+    # 检查输入文件是否存在
+    if not os.path.exists(input_path):
+        raise FileNotFoundError(f"输入文件不存在: {input_path}")
+
+    # 如果没有指定输出路径，自动生成
+    if output_path is None:
+        input_path_obj = Path(input_path)
+        output_path = input_path_obj.with_suffix('.safetensors')
+
+    print(f"正在加载模型: {input_path}")
+
+    # 尝试检测文件类型并加载
+    model_weights = None
+
+    # 首先尝试作为 TorchScript 模型加载
+    try:
+        print("尝试加载 TorchScript 模型...")
+        model = torch.jit.load(input_path, map_location='cpu')
+        print("成功加载 TorchScript 模型，提取 state_dict...")
+        model_weights = model.state_dict()
+    except:
+        # 如果失败，尝试作为普通 state_dict 加载
+        try:
+            print("尝试加载普通 state_dict...")
+            model_weights = torch.load(input_path, map_location='cpu', weights_only=False)
+        except Exception as e:
+            raise RuntimeError(f"无法加载模型文件: {e}")
+
+    # 如果是完整的模型（包含 state_dict），提取 state_dict
+    if isinstance(model_weights, dict) and 'state_dict' in model_weights:
+        print("检测到完整模型，提取 state_dict...")
+        model_weights = model_weights['state_dict']
+
+    print(f"正在保存为 safetensors 格式: {output_path}")
+
+    # 添加默认元数据
+    if metadata is None:
+        metadata = {}
+
+    # 保存为 safetensors
+    save_file(model_weights, output_path, metadata=metadata)
+
+    print(f"[OK] 转换完成！")
+    print(f"   输入文件: {input_path}")
+    print(f"   输出文件: {output_path}")
+
+    # 显示文件大小对比
+    input_size = os.path.getsize(input_path) / (1024 * 1024)
+    output_size = os.path.getsize(output_path) / (1024 * 1024)
+    print(f"\n文件大小对比:")
+    print(f"   原始文件: {input_size:.2f} MB")
+    print(f"   safetensors: {output_size:.2f} MB")
+    print(f"   压缩率: {(1 - output_size/input_size) * 100:.1f}%")
+
+
+if __name__ == "__main__":
+    # 转换当前目录下的模型
+    input_model = "chordia_v0.0.1-alpha.pt"
+    output_model = "chordia_v0.0.1-alpha.safetensors"
+
+    convert_to_safetensors(
+        input_path=input_model,
+        output_path=output_model,
+        metadata={
+            "model_name": "Chordia",
+            "version": "v0.0.1-alpha",
+            "format": "safetensors"
+        }
+    )