Comments (3)
Model not trained using Gensim you have to load it using this code then pass that model:
E.g
from gensim.models import Word2Vec
model = Word2Vec.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True, norm_only=True)
from textaugment import Word2vec
t = Word2vec(model=model)
from textaugment.
The problem might be how you saved your model. See. Try building the model in the same notebook and test.
from textaugment.
The problem might be how you saved your model. See. Try building the model in the same notebook and test.
I tried even loading the ' Google News from Google drive' but it throws error UnpicklingError: invalid load key, '3'
.
from textaugment.
Related Issues (20)
- HTTPError: HTTP Error 429: Too Many Requests
- Augmentation support for Chinese text HOT 2
- Augmenting Data with Mixup for Text Classification HOT 1
- Random State, reproducible augmentations
- `add_word` method returns `None` after 10 tries getting synonyms HOT 3
- Make it possible to set top_n in most_similar words HOT 4
- Questions about the mixup strategy HOT 3
- Possibly conflict with gensim 4.0.1 HOT 4
- Augmentation support for french text HOT 1
- Traslation: HTTPError: HTTP Error 404: Not Found HOT 3
- AttributeError: 'FastTextKeyedVectors' object has no attribute 'wv' suppose due to Migration from Gensin 3.x to 4 HOT 5
- Make a new release HOT 6
- Feature: Avoid dependency hell - break down dependencies, move some to optional
- No module named 'textblob.translate' HOT 2
- Auto download of gensim models
- add library to pip HOT 1
- Test word2vec, since i added geometric. HOT 1
- get travis.yml running tests HOT 2
- Update unit-test scripts HOT 3
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from textaugment.