Ahmadzei's picture
added 3 more tables for large emb model
5fa1a76
fill_mask = pipeline(task="fill-mask")
preds = fill_mask(text, top_k=1)
preds = [
{
"score": round(pred["score"], 4),
"token": pred["token"],
"token_str": pred["token_str"],
"sequence": pred["sequence"],
}
for pred in preds
]
preds
[{'score': 0.2236,
'token': 1761,
'token_str': ' platform',
'sequence': 'Hugging Face is a community-based open-source platform for machine learning.'}]