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| author | Mitja Felicijan <mitja.felicijan@gmail.com> | 2026-02-12 20:57:17 +0100 |
|---|---|---|
| committer | Mitja Felicijan <mitja.felicijan@gmail.com> | 2026-02-12 20:57:17 +0100 |
| commit | b333b06772c89d96aacb5490d6a219fba7c09cc6 (patch) | |
| tree | 211df60083a5946baa2ed61d33d8121b7e251b06 /llama.cpp/tools/mtmd/legacy-models/glmedge-surgery.py | |
| download | llmnpc-b333b06772c89d96aacb5490d6a219fba7c09cc6.tar.gz | |
Engage!
Diffstat (limited to 'llama.cpp/tools/mtmd/legacy-models/glmedge-surgery.py')
| -rw-r--r-- | llama.cpp/tools/mtmd/legacy-models/glmedge-surgery.py | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/llama.cpp/tools/mtmd/legacy-models/glmedge-surgery.py b/llama.cpp/tools/mtmd/legacy-models/glmedge-surgery.py new file mode 100644 index 0000000..16bb915 --- /dev/null +++ b/llama.cpp/tools/mtmd/legacy-models/glmedge-surgery.py @@ -0,0 +1,33 @@ +import argparse +import os +import torch +from transformers import AutoModel + +ap = argparse.ArgumentParser() +ap.add_argument("-m", "--model", help="Path to GLM model") +args = ap.parse_args() + +# find the model part that includes the the multimodal projector weights +model = AutoModel.from_pretrained(args.model, trust_remote_code=True, local_files_only=True) +checkpoint = model.state_dict() + +# get a list of mm tensor names +mm_tensors = [k for k, v in checkpoint.items() if k.startswith("vision.adapter.")] + +# store these tensors in a new dictionary and torch.save them +projector = {name: checkpoint[name].float() for name in mm_tensors} +torch.save(projector, f"{args.model}/glm.projector") + +clip_tensors = [k for k, v in checkpoint.items() if k.startswith("vision.vit.model.vision_model.")] +if len(clip_tensors) > 0: + clip = {name.replace("vision.vit.model.", ""): checkpoint[name].float() for name in clip_tensors} + torch.save(clip, f"{args.model}/glm.clip") + + # added tokens should be removed to be able to convert Mistral models + if os.path.exists(f"{args.model}/added_tokens.json"): + with open(f"{args.model}/added_tokens.json", "w") as f: + f.write("{}\n") + +print("Done!") +print(f"Now you can convert {args.model} to a regular LLaMA GGUF file.") +print(f"Also, use {args.model}glm.projector to prepare a glm-encoder.gguf file.") |
