from transformers import pipeline


pipeline = pipeline(
    task="fill-mask",
    model="vinai/bertweet-base",
    device=0
)
pipeline("Plants create <mask> through a process known as photosynthesis.")

import torch

from transformers import AutoModelForMaskedLM, AutoTokenizer


tokenizer = AutoTokenizer.from_pretrained(
   "vinai/bertweet-base",
)
model = AutoModelForMaskedLM.from_pretrained(
    "vinai/bertweet-base",
    device_map="auto"
)
inputs = tokenizer("Plants create <mask> through a process known as photosynthesis.", return_tensors="pt").to(model.device)

with torch.no_grad():
    outputs = model(**inputs)
    predictions = outputs.logits

masked_index = torch.where(inputs['input_ids'] == tokenizer.mask_token_id)[1]
predicted_token_id = predictions[0, masked_index].argmax(dim=-1)
predicted_token = tokenizer.decode(predicted_token_id)

print(f"The predicted token is: {predicted_token}")