add sentence transformers configs

#4
by michaelfeil - opened
Files changed (4) hide show
  1. 1_Pooling/config.json +7 -0
  2. README.md +11 -1
  3. modules.json +20 -0
  4. sentence_bert_config.json +4 -0
1_Pooling/config.json ADDED
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+ {
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+ "word_embedding_dimension": 384,
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+ "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": true,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false
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+ }
README.md CHANGED
@@ -2671,4 +2671,14 @@ If you find our paper or models helpful, please consider cite as follows:
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  ## Limitations
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- This model only works for English texts. Long texts will be truncated to at most 512 tokens.
 
 
 
 
 
 
 
 
 
 
 
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  ## Limitations
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+ This model only works for English texts. Long texts will be truncated to at most 512 tokens.
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+
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+ ## Sentence Transformers
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+
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+ Below is an example for usage with sentence_transformers. `pip install sentence_transformers~=2.2.2`
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+ This is community contributed, and results may vary up to numerical precision.
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+ ```python
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+ from sentence_transformers import SentenceTransformer
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+ model = SentenceTransformer('intfloat/e5-small-v2')
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+ embeddings = model.encode(input_texts, normalize_embeddings=True)
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+ ```
modules.json ADDED
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+ [
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+ {
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+ "idx": 0,
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+ "name": "0",
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+ "path": "",
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+ "type": "sentence_transformers.models.Transformer"
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+ },
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+ {
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+ "idx": 1,
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+ "name": "1",
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+ "path": "1_Pooling",
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+ "type": "sentence_transformers.models.Pooling"
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+ },
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+ {
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+ "idx": 2,
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+ "name": "2",
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+ "path": "2_Normalize",
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+ "type": "sentence_transformers.models.Normalize"
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+ }
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+ ]
sentence_bert_config.json ADDED
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+ {
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+ "max_seq_length": 512,
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+ "do_lower_case": false
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+ }