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from DLM_emb_model import MolEmbDLM
from transformers import AutoTokenizer
import torch
MODEL_DIR = "Kiria-Nozan/ApexOracle"
tokenizer = AutoTokenizer.from_pretrained(MODEL_DIR)
model = MolEmbDLM.from_pretrained(MODEL_DIR)
model.eval()
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
model = model.to(device)
seq = "[C][C][O]" # ← 替换成你的输入串
batch = tokenizer(
seq.replace('][', '] ['),
padding=False,
truncation=False,
return_tensors="pt",
)
print(batch)
batch.to(device)
with torch.no_grad():
embeddings = model(
input_ids=batch["input_ids"],
attention_mask=batch["attention_mask"],
) # (1, seq_len, hidden_size)
print(embeddings.shape) |