| """Save the ORIGINAL VideoLLaMA3-7B mm_projector weights to a small file. |
| |
| Phase-1 fine-tuned mm_projector (lr 5e-6) on compressed tokens only; raw (uncompressed) |
| frames are projected with the original VideoLLaMA3 projector instead (vbe/infer.py). |
| The vision encoder and the LLM are bit-identical between the two checkpoints. |
| |
| python scripts/extract_orig_projector.py \ |
| /workspace/chicheng/OnlineLong/pretrained_models/videollama3_7b_local checkpoints/vl3_orig_projector.pt |
| """ |
| import os |
| import sys |
|
|
| import torch |
|
|
| src, dst = sys.argv[1], sys.argv[2] |
| path = os.path.join(src, "pytorch_model.bin") |
| if os.path.exists(path): |
| sd = torch.load(path, map_location="cpu", mmap=True, weights_only=True) |
| else: |
| from safetensors.torch import load_file |
| import json |
| index = json.load(open(os.path.join(src, "model.safetensors.index.json")))["weight_map"] |
| files = {f for k, f in index.items() if k.startswith("model.mm_projector.")} |
| sd = {} |
| for f in files: |
| sd.update(load_file(os.path.join(src, f))) |
| proj = {k[len("model.mm_projector."):]: v.clone() for k, v in sd.items() if k.startswith("model.mm_projector.")} |
| assert proj, f"no model.mm_projector.* weights in {src}" |
| os.makedirs(os.path.dirname(os.path.abspath(dst)), exist_ok=True) |
| torch.save(proj, dst) |
| print(f"saved {sorted(proj)} -> {dst}") |
|
|
