Comments (3)
svjan5
commented on September 12, 2024
Yes, the model gives the embeddings similar to word2vec and GloVe.
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eyuansu62
commented on September 12, 2024
I got it. So if I want to use the model to encode the text to get its embeddings representation, can I directly use the embeddings.txt I trained?
Or is it similar to BERT used as an encoder? which can I fine-tuned on my tasks or using the best model you mentioned in ISSUE #16 as an encoder when I want to get the vector representation of texts?
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svjan5
commented on September 12, 2024
Yes, you can use 'embedding.txt' directly. The model is similar to word2vec, not ELMo/BERT.
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Related Issues (20)
- Detailed experimental parameters settings HOT 1
- Segmentation fault (core dumped) HOT 20
- how to build a syntactic graph HOT 1
- Would it possible for you to release your pre-trained model checkpoint? HOT 6
- About the gating mechanism HOT 5
- About the stopping criteria HOT 1
- Reproduction Problem HOT 5
- urllib.error.URLError HOT 1
- If i just want to train the model, do i need to replace the data? HOT 1
- StopIteration error from referenced web package in python 3.7.0
- “from web.embedding import Embedding” What package for this？ HOT 1
- Verse BERT HOT 1
- Issue with GetBatches function HOT 4
- How do you acquire semantic_info? HOT 2
- Question about the edge direction in SemGCN HOT 2
- from models import model？？？ HOT 1
- i need help！！！ HOT 2
- About SemGCN embeddings HOT 1
- About using own text data for SynGCN and SemGCN HOT 1
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