huggingface / huggingface/sentence-transformers
Regarding embedding returned by the model
Open
- Dominant language
- Python
- Stars
- 19.1k
- Forks
- 2.9k
- Avg merge
- 1d 19h
- Merged PRs (30d)
- 61
Description
I am loading bert-base-nli-mean-tokens model to get the embedding of the sentence. I had a question, from which layer of the bert base model you are taking the embedding that is being returned by the bert-base-nli-mean-token model. Please let me know.
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by tracing how the bert-base-nli-mean-tokens model produces its returned sentence embedding. Document which BERT layer or output is used, and make the explanation easy to find for users of this model.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface, python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100