Issues while loading a trained fasttext model using gensim

Question

I am trying to load a trained fasttext model using gensim. The model has been trained on some data. Earlier, I have used model.save() with a extension of .bin to use it later. After the training process and saving the model using model.save in .bin format, generates 3 files respectively. They are:

1) .bin

2) bin.trainable vectors_ngrams_lockf

3) bin.wv.vectors_ngrams

Now I am unable to load the trained binary file (.bin).

But I don't understand why I am getting a error named:

raise NotImplementedError("Supervised fastText models are not supported") NotImplementedError: Supervised fastText models are not supported

After going through many blogs, peoples have suggested that gensim does not supports supervised training. It's fine. My question is how can I be able to load the trained binary model. Shall I need to train the model differently.

Any help is appreciated.

What I have tried after the training process:

import logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
from gensim.models import FastText, fasttext
model = FastText.load_fasttext_format('m1.bin')
print(model)

Answer 1

如果模型中保存gensim的原生.save()方法，你会与加载.load() -未load_fasttext_format()它仅用于保存在由Facebook的原FastText C ++代码中使用RAW格式的机型。