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This repository has been archived by the owner on Oct 31, 2023. It is now read-only.
from models import InferSent
import torch
model_version = 1
MODEL_PATH = "/home/encoder/infersent1.pkl"
params_model = {'bsize': 64, 'word_emb_dim': 300, 'enc_lstm_dim': 2048,
'pool_type': 'max', 'dpout_model': 0.0, 'version': model_version}
model = InferSent(params_model)
model.load_state_dict(torch.load(MODEL_PATH))
use_cuda = False
model = model.cuda() if use_cuda else model
W2V_PATH = '/home/GLOVE/glove.6B/glove.6B.300d.txt'
model.set_w2v_path(W2V_PATH)
model.build_vocab_k_words(K=100000)
# Load some sentences
sentences = ["I ate dinner.",
"We had a three-course meal.",
"Brad came to dinner with us.",
"He loves fish tacos.",
"In the end, we all felt like we ate too much.",
"We all agreed; it was a magnificent evening."]
with open('samples.txt') as f:
for line in f:
sentences.append(line.strip())
print(len(sentences))
embeddings = model.encode(sentences, bsize=128, tokenize=False, verbose=True)
print('nb sentences encoded : {0}'.format(len(embeddings)))
But it showed the error KeyError: '</s>'.
Where i got wrong?
The text was updated successfully, but these errors were encountered:
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Tried the below code
But it showed the error
KeyError: '</s>'
.Where i got wrong?
The text was updated successfully, but these errors were encountered: