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How to continue the pretraining of Sentence-BERT models using MLM?
Is there any documentation or code snippet for this purpose?
I would like to continue the pretraining of "all-MiniLM-L6-v2" mode…
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I finetuned some embedding and perform some subtraction above a subset of some sentence’s embedding.
These sentences are similar in the sense of edit distance.
And i hope this will perform some sens…
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When calling:
model = SentenceTransformer('distilbert-base-nli-stsb-mean-tokens')
I consistently receive timeout errors.
MaxRetryError: HTTPSConnectionPool(host='sbert.net', port=443): Max re…
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[yunjinchoidev]
![232969785-a39a59d7-077a-4e0b-8d26-d5194259df72](https://user-images.githubusercontent.com/89494907/233949591-59c2e38a-5562-412a-ab94-83f970fca1cd.png)
![232970200-9bbecfb8-833d…
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In the [SBERT repository](https://www.sbert.net/examples/training/adaptive_layer/README.html), I found the adaptive layers method referenced in this paper: [_**ESE**: Espresso Sentence Embeddings_](ht…
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As a user, I can ask a natural language question of the chatbot, and it will search a defined knowledge base, retrieving the best match, and summarizing the specific section which triggered the match.…
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Relation Model_includes_Model is the most problematic relation. It's clear that we need to improve prompt for better relation extraction
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I have about 6 million sentences and my embedding vector size is 768 using SBERT.
The problem is that embedding data is too large! (6 million sentences produce about over 200 GB)
I never knew that a…
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Hey,
it is the second time I encounter low results for specific models. In short, I once trained `deepset/gbert-base` with `train_msmarco_v3_margin_MSE.py` and it worked like a charm. Then I tried …
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**Is your feature request related to a problem? Please describe.**
Cursor seems like a really interesting idea and the integration points look really good. The ability to provide my own OpenAI key …