radlab
/

polish-sts-v2

Sentence Similarity

sentence-transformers

feature-extraction

Inference Endpoints

text-embeddings-inference

Model card Files Files and versions Community

pkedzia commited on Dec 3, 2023

Commit

e591d17

•

1 Parent(s): 6605159

Update README.md

Files changed (1) hide show

README.md +4 -3

README.md CHANGED Viewed

@@ -7,7 +7,7 @@ tags:
 - transformers
 language:
 - pl
-license: lgpl-3.0
 library_name: sentence-transformers
 datasets:
 - radlab/polish-sts-dataset
@@ -20,7 +20,8 @@ models:
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 As a base model `sdadas/polish-roberta-large-v2` model was used.
-<!--- Describe your model here -->
 ## Usage (Sentence-Transformers)
@@ -118,4 +119,4 @@ SentenceTransformer(
   (0): Transformer({'max_seq_length': 514, 'do_lower_case': False}) with Transformer model: RobertaModel
   (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
 )
-```

 - transformers
 language:
 - pl
+license: cc-by-sa-4.0
 library_name: sentence-transformers
 datasets:
 - radlab/polish-sts-dataset
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 As a base model `sdadas/polish-roberta-large-v2` model was used.
+This model is **deprecated** and has been replaced by [radlab/polish-bi-encoder-mean](https://huggingface.co/radlab/polish-bi-encoder-mean).
 ## Usage (Sentence-Transformers)
   (0): Transformer({'max_seq_length': 514, 'do_lower_case': False}) with Transformer model: RobertaModel
   (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
 )
+```