3D-GRAND / llava /model /utils.py
jedyang97's picture
initial demo
947767a
from transformers import AutoConfig
def auto_upgrade(config):
cfg = AutoConfig.from_pretrained(config)
if "llava" in config and "llava" not in cfg.model_type:
assert cfg.model_type == "llama"
print(
"You are using newer LLaVA code base, while the checkpoint of v0 is from older code base."
)
print(
"You must upgrade the checkpoint to the new code base (this can be done automatically)."
)
confirm = input("Please confirm that you want to upgrade the checkpoint. [Y/N]")
if confirm.lower() in ["y", "yes"]:
print("Upgrading checkpoint...")
assert len(cfg.architectures) == 1
setattr(cfg.__class__, "model_type", "llava")
cfg.architectures[0] = "LlavaLlamaForCausalLM"
cfg.save_pretrained(config)
print("Checkpoint upgraded.")
else:
print("Checkpoint upgrade aborted.")
exit(1)
def get_w(weights, keyword):
return {
k.split(keyword + ".", maxsplit=1)[1]: v
for k, v in weights.items()
if keyword in k
}