convert-*.py: autogenerate general.uuid if missing

convert_hf_to_gguf.py

@@ -381,6 +381,12 @@ def prepare_metadata(self, vocab_only: bool):
                 # output in the same directory as the model by default
                 self.fname_out = self.dir_model / f"{fname_default}.gguf"
 
+        # Upon missing model uuid, generate uuid based on tensor content
+        if not vocab_only and self.metadata.uuid is None:
+            self.metadata.uuid = self.gguf_writer.generate_tensors_uuid()
+            max_name_len = max(len(s) for _, s in self.tensor_map.mapping.values()) + len(".weight,")
+            logger.info(f"{f'%-{max_name_len}s' % f'generating general.uuid'} {self.metadata.uuid}")
+
         self.set_type()
 
         logger.info("Set meta model")

gguf-py/gguf/gguf_writer.py

@@ -2,6 +2,8 @@
 
 import logging
 import os
+import uuid
+import hashlib
 import shutil
 import struct
 import tempfile
@@ -417,6 +419,19 @@ def write_tensor_data(self, tensor: np.ndarray[Any, Any]) -> None:
 
         self.state = WriterState.WEIGHTS
 
+    def generate_tensors_uuid(self) -> str:
+        uuidv5_sha1 = hashlib.sha1()
+        uuidv5_sha1.update(uuid.UUID('ef001206-dadc-5f6d-a15f-3359e577d4e5').bytes)
+
+        for tensors in self.tensors:
+            # relying on the fact that Python dicts preserve insertion order (since 3.7)
+            for name, ti in tensors.items():
+                assert ti.tensor is not None
+                assert ti.tensor.nbytes == ti.nbytes
+                uuidv5_sha1.update(ti.tensor.tobytes('C'))
+
+        return str(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5))
+
     def write_tensors_to_file(self, *, progress: bool = False) -> None:
         self.write_ti_data_to_file()