Sentence Similarity
sentence-transformers
PyTorch
roberta
feature-extraction
text-embeddings-inference
Instructions to use codecompletedeployment/st-codesearch-distilroberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use codecompletedeployment/st-codesearch-distilroberta-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codecompletedeployment/st-codesearch-distilroberta-base") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Commit ·
dfd4dea
1
Parent(s): ab8b41c
change to cls_embeding
Browse files- 1_Pooling/config.json +2 -2
1_Pooling/config.json
CHANGED
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@@ -1,7 +1,7 @@
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token":
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"pooling_mode_mean_tokens":
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false
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}
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": true,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false
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}
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