summaryrefslogtreecommitdiff
path: root/examples/llava/llava-surgery.py
diff options
context:
space:
mode:
Diffstat (limited to 'examples/llava/llava-surgery.py')
-rw-r--r--examples/llava/llava-surgery.py30
1 files changed, 30 insertions, 0 deletions
diff --git a/examples/llava/llava-surgery.py b/examples/llava/llava-surgery.py
new file mode 100644
index 00000000..26294d9b
--- /dev/null
+++ b/examples/llava/llava-surgery.py
@@ -0,0 +1,30 @@
+import argparse
+import glob
+import os
+import torch
+
+
+ap = argparse.ArgumentParser()
+ap.add_argument("-m", "--model", help="Path to LLaVA v1.5 model")
+args = ap.parse_args()
+
+# find the model part that includes the the multimodal projector weights
+path = sorted(glob.glob(f"{args.model}/pytorch_model*.bin"))[-1]
+checkpoint = torch.load(path)
+
+# get a list of mm tensor names
+mm_tensors = [k for k, v in checkpoint.items() if k.startswith("model.mm_projector")]
+
+# store these tensors in a new dictionary and torch.save them
+projector = {name: checkpoint[name] for name in mm_tensors}
+torch.save(projector, f"{args.model}/llava.projector")
+
+# remove these tensors from the checkpoint and save it again
+for name in mm_tensors:
+ del checkpoint[name]
+
+torch.save(checkpoint, path)
+
+print("Done!")
+print(f"Now you can convert {args.model} to a a regular LLaMA GGUF file.")
+print(f"Also, use {args.model}/llava.projector to prepare a llava-encoder.gguf file.")