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Comments (2)

mariisaschmidt avatar mariisaschmidt commented on August 22, 2024 1

Hi!
vielen Dank! So klappt es! 😄

from germanwordembeddings.

devmount avatar devmount commented on August 22, 2024

Hi Marisa,
spannendes Projekt! Ich habe das Model damals im word2vec C binary Format gespeichert, es muss auch in diesem Format geladen werden, damit es funktioniert. Ich habe deinen Code geprüft, du lädst das Model per

vector_model = gensim.models.Word2Vec.load(w2v_model).wv

Damals habe ich es so geladen:

GermanWordEmbeddings/evaluation.py

Line 332 in e39c8bf

trained_model = gensim.models.KeyedVectors.load_word2vec_format(args.model.strip(), binary=is_binary)

Ich habe mal in die Doku geschaut und gesehen, dass das C binary Format anscheinend noch unterstützt wird. Hier ein Beispiel für das Laden in deinem Fall (ungetestet):

from gensim.test.utils import datapath
vector_model = gensim.models.KeyedVectors.load_word2vec_format(datapath(w2v_model), binary=True)

from germanwordembeddings.

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