chore: import upstream snapshot with attribution

2026-07-13 12:35:23 +08:00
commit 1f0f055804
72 changed files with 147370 additions and 0 deletions
@@ -0,0 +1,50 @@
+from safetensors import safe_open
+from safetensors.torch import save_file
+import torch
+
+def quant_weight_fp16(weight):
+    weight = weight.to(torch.float)
+    s = 1.0 / weight.abs().mean().clamp_(min=1e-5)
+    new_weight = (weight * s).round().clamp(-1, 1) / s
+    return new_weight
+
+def quant_model(input, output):
+    tensors = {}
+
+    with safe_open(input, framework='pt') as f:
+        for name in f.keys():
+            tensors[name] = f.get_tensor(name)
+
+            keyword_list = [
+                'q_proj.weight', 
+                'k_proj.weight', 
+                'v_proj.weight',
+                'o_proj.weight',
+                'gate_proj.weight',
+                'up_proj.weight',
+                'down_proj.weight'
+            ]
+
+            if any(keyword in name for keyword in keyword_list):
+                print(f'[INFO] Quantizing {name}')
+                tensors[name] = quant_weight_fp16(tensors[name])
+    
+    print(f'[INFO] Saving to {output}\nThis may take a while.')
+    save_file(tensors, output)
+                
+
+if __name__ == "__main__":
+    import argparse
+    parser = argparse.ArgumentParser(description="Convert Safetensors back to Torch .pth checkpoint")
+    parser.add_argument(
+        "--input", type=str, required=True,
+    )
+    parser.add_argument(
+        "--output", type=str, required=True,
+    )
+    args = parser.parse_args()
+
+    quant_model(
+        input=args.input,
+        output=args.output,
+    )