Add new SentenceTransformer model.

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "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,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

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+---
+language: []
+library_name: sentence-transformers
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:46453
+- loss:MultipleNegativesRankingLoss
+base_model: sentence-transformers/all-mpnet-base-v2
+datasets: []
+widget:
+- source_sentence: clinician thinks the patient is homeless
+  sentences:
+  - '- Ms. ___ was homeless at the time of this admission.'
+  - This is ___ year old single homeless woman, previously diagnosed with borderline
+    personality disorder with chronic affective instability, reactive mood, impulsivity,
+    SIB (ingesting objects while hospitalized), recently discharged from ___ on ___,
+    ___ client, who presented to ___ on a ___ with worsening mood, threats of suicide
+    via cutting her legs off, as well as thoughts of wanting to hurt _
+  - Patient reports that her apartment is bugged, she has camera in her television,
+    and a helicopter is reading minds.
+- source_sentence: assigned a case manager for housing
+  sentences:
+  - 'Home With Service Facility:'
+  - We consulted social work, psychiatry, and the case managers, who are working with
+    the hospital attorneys to acquire safer housing options with greater oversight
+    from health care professionals. .
+  - Has not established care with
+- source_sentence: has been homeless
+  sentences:
+  - He reports being homeless, living in an empty garage near his sister.
+  - To complicate matters, patient's main support/roommate will be moving out of country
+    soon, so he will no longer be able to live in his apartment.
+  - 'Axis IV: homelessness'
+- source_sentence: homelessness
+  sentences:
+  - Does not identify any acute stressors, but describes no longer being able to tolerate
+    being homeless (lack of food/clothing/showers).
+  - Unclear how reliable his group home is administering meds, notably nursing is
+    quite limited.
+  - Case management assisted in formulated a plan with ___ that would allow the patient's
+    ___ be the first responder when issues regarding her these two problems arise.
+- source_sentence: assisted…housing benefits
+  sentences:
+  - As a result, patient is currently homeless.
+  - 'Home With Service Facility:'
+  - Patient with multiple admissions in the past several months, homeless.
+pipeline_tag: sentence-similarity
+---
+
+# SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) <!-- at revision 84f2bcc00d77236f9e89c8a360a00fb1139bf47d -->
+- **Maximum Sequence Length:** 384 tokens
+- **Output Dimensionality:** 768 tokens
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 384, 'do_lower_case': False}) with Transformer model: MPNetModel 
+  (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, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+  (2): Normalize()
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("Shobhank-iiitdwd/Clinical_sentence_transformers_mpnet_base_v2")
+# Run inference
+sentences = [
+    'assisted…housing benefits',
+    'Home With Service Facility:',
+    'Patient with multiple admissions in the past several months, homeless.',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 768]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+
+* Size: 46,453 training samples
+* Columns: <code>sentence_0</code> and <code>sentence_1</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence_0                                                                       | sentence_1                                                                         |
+  |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
+  | type    | string                                                                           | string                                                                             |
+  | details | <ul><li>min: 3 tokens</li><li>mean: 6.64 tokens</li><li>max: 11 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 23.81 tokens</li><li>max: 384 tokens</li></ul> |
+* Samples:
+  | sentence_0                          | sentence_1                                                                                                                                                                                                                                                         |
+  |:------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>has been homeless</code>      | <code>He has a GED level education and previously held a stable job for a ___. However, mother reports he recently quit his job suddenly and is homeless right now after multiple family members kicked him out of their homes.</code>                             |
+  | <code>gave list of shelters</code>  | <code>Home With Service Facility:</code>                                                                                                                                                                                                                           |
+  | <code>assessed housing needs</code> | <code>Patient with longstanding history of instrumental suicidal ideation and waxing and waning symptoms of depression and anxiety, SI when his needs, particularly regarding housing, are not being met with documented history of quick retraction of his</code> |
+* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 64
+- `per_device_eval_batch_size`: 64
+- `num_train_epochs`: 100
+- `multi_dataset_batch_sampler`: round_robin
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: no
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 64
+- `per_device_eval_batch_size`: 64
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `learning_rate`: 5e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1
+- `num_train_epochs`: 100
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.0
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: False
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: False
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: round_robin
+
+</details>
+
+### Training Logs
+<details><summary>Click to expand</summary>
+
+| Epoch   | Step  | Training Loss |
+|:-------:|:-----:|:-------------:|
+| 0.6887  | 500   | 3.5133        |
+| 1.3774  | 1000  | 3.2727        |
+| 2.0661  | 1500  | 3.2238        |
+| 2.7548  | 2000  | 3.1758        |
+| 3.4435  | 2500  | 3.1582        |
+| 4.1322  | 3000  | 3.1385        |
+| 4.8209  | 3500  | 3.1155        |
+| 5.5096  | 4000  | 3.1034        |
+| 6.1983  | 4500  | 3.091         |
+| 6.8871  | 5000  | 3.0768        |
+| 7.5758  | 5500  | 3.065         |
+| 8.2645  | 6000  | 3.0632        |
+| 8.9532  | 6500  | 3.0566        |
+| 9.6419  | 7000  | 3.0433        |
+| 0.6887  | 500   | 3.0536        |
+| 1.3774  | 1000  | 3.0608        |
+| 2.0661  | 1500  | 3.0631        |
+| 2.7548  | 2000  | 3.0644        |
+| 3.4435  | 2500  | 3.0667        |
+| 4.1322  | 3000  | 3.07          |
+| 4.8209  | 3500  | 3.0682        |
+| 5.5096  | 4000  | 3.0718        |
+| 6.1983  | 4500  | 3.0719        |
+| 6.8871  | 5000  | 3.0685        |
+| 7.5758  | 5500  | 3.0723        |
+| 8.2645  | 6000  | 3.0681        |
+| 8.9532  | 6500  | 3.0633        |
+| 9.6419  | 7000  | 3.0642        |
+| 10.3306 | 7500  | 3.0511        |
+| 11.0193 | 8000  | 3.0463        |
+| 11.7080 | 8500  | 3.0301        |
+| 12.3967 | 9000  | 3.0163        |
+| 13.0854 | 9500  | 3.0059        |
+| 13.7741 | 10000 | 2.9845        |
+| 14.4628 | 10500 | 2.9705        |
+| 15.1515 | 11000 | 2.9536        |
+| 15.8402 | 11500 | 2.9263        |
+| 16.5289 | 12000 | 2.9199        |
+| 17.2176 | 12500 | 2.8989        |
+| 17.9063 | 13000 | 2.8818        |
+| 18.5950 | 13500 | 2.8735        |
+| 19.2837 | 14000 | 2.852         |
+| 19.9725 | 14500 | 2.8315        |
+| 20.6612 | 15000 | 2.8095        |
+| 21.3499 | 15500 | 2.7965        |
+| 22.0386 | 16000 | 2.7802        |
+| 22.7273 | 16500 | 2.7527        |
+| 23.4160 | 17000 | 2.7547        |
+| 24.1047 | 17500 | 2.7377        |
+| 24.7934 | 18000 | 2.7035        |
+| 25.4821 | 18500 | 2.7102        |
+| 26.1708 | 19000 | 2.6997        |
+| 26.8595 | 19500 | 2.6548        |
+| 27.5482 | 20000 | 2.6704        |
+| 28.2369 | 20500 | 2.6624        |
+| 28.9256 | 21000 | 2.6306        |
+| 29.6143 | 21500 | 2.6358        |
+| 30.3030 | 22000 | 2.634         |
+| 30.9917 | 22500 | 2.6089        |
+| 31.6804 | 23000 | 2.607         |
+| 32.3691 | 23500 | 2.6246        |
+| 33.0579 | 24000 | 2.5947        |
+| 33.7466 | 24500 | 2.5798        |
+| 34.4353 | 25000 | 2.6025        |
+| 35.1240 | 25500 | 2.5824        |
+| 35.8127 | 26000 | 2.5698        |
+| 36.5014 | 26500 | 2.5711        |
+| 37.1901 | 27000 | 2.5636        |
+| 37.8788 | 27500 | 2.5387        |
+| 38.5675 | 28000 | 2.5472        |
+| 39.2562 | 28500 | 2.5455        |
+| 39.9449 | 29000 | 2.5204        |
+| 40.6336 | 29500 | 2.524         |
+| 41.3223 | 30000 | 2.5246        |
+| 42.0110 | 30500 | 2.5125        |
+| 42.6997 | 31000 | 2.5042        |
+| 43.3884 | 31500 | 2.5165        |
+| 44.0771 | 32000 | 2.5187        |
+| 44.7658 | 32500 | 2.4975        |
+| 45.4545 | 33000 | 2.5048        |
+| 46.1433 | 33500 | 2.521         |
+| 46.8320 | 34000 | 2.4825        |
+| 47.5207 | 34500 | 2.5034        |
+| 48.2094 | 35000 | 2.5049        |
+| 48.8981 | 35500 | 2.4886        |
+| 49.5868 | 36000 | 2.4992        |
+| 50.2755 | 36500 | 2.5099        |
+| 50.9642 | 37000 | 2.489         |
+| 51.6529 | 37500 | 2.4825        |
+| 52.3416 | 38000 | 2.4902        |
+| 53.0303 | 38500 | 2.4815        |
+| 53.7190 | 39000 | 2.4723        |
+| 54.4077 | 39500 | 2.4921        |
+| 55.0964 | 40000 | 2.4763        |
+| 55.7851 | 40500 | 2.4692        |
+| 56.4738 | 41000 | 2.4831        |
+| 57.1625 | 41500 | 2.4705        |
+| 57.8512 | 42000 | 2.4659        |
+| 58.5399 | 42500 | 2.4804        |
+| 59.2287 | 43000 | 2.4582        |
+| 59.9174 | 43500 | 2.4544        |
+| 60.6061 | 44000 | 2.4712        |
+| 61.2948 | 44500 | 2.4478        |
+| 61.9835 | 45000 | 2.4428        |
+| 62.6722 | 45500 | 2.4558        |
+| 63.3609 | 46000 | 2.4428        |
+| 64.0496 | 46500 | 2.4399        |
+| 64.7383 | 47000 | 2.4529        |
+| 65.4270 | 47500 | 2.4374        |
+| 66.1157 | 48000 | 2.4543        |
+| 66.8044 | 48500 | 2.4576        |
+| 67.4931 | 49000 | 2.4426        |
+| 68.1818 | 49500 | 2.4698        |
+| 68.8705 | 50000 | 2.4604        |
+| 69.5592 | 50500 | 2.4515        |
+| 70.2479 | 51000 | 2.4804        |
+| 70.9366 | 51500 | 2.4545        |
+| 71.6253 | 52000 | 2.4523        |
+| 72.3140 | 52500 | 2.4756        |
+| 73.0028 | 53000 | 2.4697        |
+| 73.6915 | 53500 | 2.4536        |
+| 74.3802 | 54000 | 2.4866        |
+| 75.0689 | 54500 | 2.471         |
+| 75.7576 | 55000 | 2.483         |
+| 76.4463 | 55500 | 2.5002        |
+| 77.1350 | 56000 | 2.4849        |
+| 77.8237 | 56500 | 2.4848        |
+| 78.5124 | 57000 | 2.5047        |
+| 79.2011 | 57500 | 2.5143        |
+| 79.8898 | 58000 | 2.4879        |
+| 80.5785 | 58500 | 2.5093        |
+| 81.2672 | 59000 | 2.5247        |
+| 81.9559 | 59500 | 2.4915        |
+| 82.6446 | 60000 | 2.5124        |
+| 83.3333 | 60500 | 2.5056        |
+| 84.0220 | 61000 | 2.4767        |
+| 84.7107 | 61500 | 2.5068        |
+| 85.3994 | 62000 | 2.5173        |
+| 86.0882 | 62500 | 2.4911        |
+| 86.7769 | 63000 | 2.526         |
+| 87.4656 | 63500 | 2.5313        |
+| 88.1543 | 64000 | 2.5312        |
+| 88.8430 | 64500 | 2.5735        |
+| 89.5317 | 65000 | 2.5873        |
+| 90.2204 | 65500 | 2.6395        |
+| 90.9091 | 66000 | 2.7914        |
+| 91.5978 | 66500 | 2.6729        |
+| 92.2865 | 67000 | 2.9846        |
+| 92.9752 | 67500 | 2.9259        |
+| 93.6639 | 68000 | 2.8845        |
+| 94.3526 | 68500 | 2.9906        |
+| 95.0413 | 69000 | 2.9534        |
+| 95.7300 | 69500 | 2.9857        |
+| 96.4187 | 70000 | 3.0559        |
+| 97.1074 | 70500 | 2.9919        |
+| 97.7961 | 71000 | 3.0435        |
+| 98.4848 | 71500 | 3.0534        |
+| 99.1736 | 72000 | 3.0169        |
+| 99.8623 | 72500 | 3.0264        |
+
+</details>
+
+### Framework Versions
+- Python: 3.10.11
+- Sentence Transformers: 3.0.1
+- Transformers: 4.41.2
+- PyTorch: 2.0.1
+- Accelerate: 0.31.0
+- Datasets: 2.19.1
+- Tokenizers: 0.19.1
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{henderson2017efficient,
+    title={Efficient Natural Language Response Suggestion for Smart Reply}, 
+    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
+    year={2017},
+    eprint={1705.00652},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,24 @@
+{
+  "_name_or_path": "./Clincial_sentence-transformers/mpnet-base-v2",
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.0.1",
+    "transformers": "4.41.2",
+    "pytorch": "2.0.1"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": null
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb1cbb0337340d47988a6d3bc4ea36ebdb6b7f920e90c393f75199842a8d12b0
+size 437967672

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 384,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,51 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,72 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "104": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "30526": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 128,
+  "model_max_length": 384,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}