Comments (2)
Hi!
vielen Dank! So klappt es! 😄
from germanwordembeddings.
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
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.
Related Issues (15)
- Function deprecated HOT 1
- RuntimeError: you must first build vocabulary before training the model HOT 5
- Error in preprocessing.py HOT 3
- UnicodeDecodeError: 'ascii' codec can't decode byte 0xc3 in position 0: ordinal not in range(128) HOT 4
- plain text to segments HOT 5
- Provide citation info HOT 5
- model evaluation & two error messages HOT 2
- saving full model? HOT 1
- Use already trained model HOT 2
- german.model done with skip-gram or CBOW? HOT 7
- Error trying to load "german.model" HOT 2
- Choose model type based on file extension HOT 4
- Tests should be lowercased HOT 6
- Invalid Load Key Error HOT 2
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from germanwordembeddings.