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Browse files- README.md +5 -5
- config.json +17 -17
- model.safetensors +2 -2
- special_tokens_map.json +49 -5
- tokenizer.json +0 -0
- tokenizer_config.json +25 -15
- vocab.txt +0 -0
README.md
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---
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#
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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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**DataLoader**:
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`torch.utils.data.dataloader.DataLoader` of length
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```
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{'batch_size':
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```
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**Loss**:
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},
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"scheduler": "WarmupLinear",
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"steps_per_epoch": null,
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"warmup_steps":
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"weight_decay": 0.01
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}
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```
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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:
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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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(2): Normalize()
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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 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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**DataLoader**:
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`torch.utils.data.dataloader.DataLoader` of length 2688 with parameters:
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```
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{'batch_size': 5, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
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```
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**Loss**:
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},
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"scheduler": "WarmupLinear",
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"steps_per_epoch": null,
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"warmup_steps": 268,
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"weight_decay": 0.01
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}
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```
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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: MPNetModel
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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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(2): Normalize()
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)
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config.json
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{
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"_name_or_path": "/root/.cache/torch/sentence_transformers/sentence-transformers_multi-qa-
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"activation": "gelu",
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"architectures": [
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],
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"initializer_range": 0.02,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"vocab_size":
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}
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"_name_or_path": "/root/.cache/torch/sentence_transformers/sentence-transformers_multi-qa-mpnet-base-cos-v1/",
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"architectures": [
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"MPNetModel"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "mpnet",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"relative_attention_num_buckets": 32,
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"vocab_size": 30527
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 437967672
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special_tokens_map.json
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{
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}
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"mask_token": {
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tokenizer.json
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tokenizer_config.json
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{
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vocab.txt
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