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README.md CHANGED
@@ -10,7 +10,7 @@ tags:
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  # {MODEL_NAME}
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- This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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  <!--- Describe your model here -->
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@@ -119,8 +119,8 @@ Parameters of the fit()-Method:
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  ## Full Model Architecture
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  ```
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  SentenceTransformer(
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- (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: DistilBertModel
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- (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
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  )
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  ```
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  # {MODEL_NAME}
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+ This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 312 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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  <!--- Describe your model here -->
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  ## Full Model Architecture
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  ```
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  SentenceTransformer(
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+ (0): Transformer({'max_seq_length': 2048, 'do_lower_case': False}) with Transformer model: BertModel
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+ (1): Pooling({'word_embedding_dimension': 312, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
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  )
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  ```
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config.json CHANGED
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  {
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- "_name_or_path": "/media/denis/042CD5B7300C3479/instructor_chatbot/models/embedding_model/",
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- "n_layers": 6,
 
 
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  "transformers_version": "4.29.2",
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  "torch_dtype": "float32",
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  "transformers_version": "4.29.2",
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  }
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