Add new SentenceTransformer model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 1024,
+  "pooling_mode_cls_token": true,
+  "pooling_mode_mean_tokens": false,
+  "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

@@ -0,0 +1,487 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:69500
+- loss:Infonce
+base_model: Snowflake/snowflake-arctic-embed-l-v2.0
+widget:
+- source_sentence: What aspect of human relationship to nature is omitted from the
+    text
+  sentences:
+  - 'There are a few good ones, though. Here are the best WWE apps and WWE games for
+    Android! The first five are the best games...
+
+    Go Android Apps (blog)
+
+    The Best Themes for Android Free Download: Hi friend we are again back with our
+    new top ten best free themes for android list. This article is especially dedicated
+    for those persons who want to make their smartphone...
+
+    Paragon Software has created an app for Android that allows your device to natively
+    read partitions in file systems that Android normally can''t handle, such as Microsoft''s
+    NTFS, allowing immediate and easy use of... While the Sentio Desktop app can be
+    used on its own, it was primarily meant to complement Sentio''s Superbook, a crowdfunded
+    laptop shell for Android smartphones and tablets that''s just entering production
+    after...
+
+    ... phone then GBWhatsapp is the app for you. GBWhatsapp is basically similar
+    to Whatsapp+ in terms of features. The newest available version right now is GBWhatsapp
+    6.40 APK for Android devices.'
+  - A true entertainer. date city state venue 11/23/2012 West Palm Beach FL Kravis
+    Center 11/24/2012 Sarasota FL Van Wezel Performing Arts Hall 11/25/2012 Clearwater
+    FL Capitol Theatre 11/29/2012 Durham NC Durham Performing Arts Center 12/1/2012
+    Atlantic City NJ Trump Taj Mahal 12/2/2012 Staten Island NY St. George Theatre
+    12/4/2012 Bethlehem PA Musikfest Cafe 12/5/2012 Verona NY Turning Stone Casino
+    12/6/2012 Stamford CT Palace Theatre Stamford 12/8/2012 Shippensburg PA Luhrs
+    Center 12/9/2012 Boston MA Wilbur Theatre 12/11/2012 Greensburg PA The Palace
+    Theatre 12/12/2012 Easton MD Avalon Theatre 12/15/2012 Saint Charles IL Arcada
+    Theater 12/16/2012 Milwaukee WI Potawatomi Bingo Casino 12/18/2012 Beaver Creek
+    CO Vilar Performing Arts Center 12/20/2012 Chandler AZ Ovations Live!
+  - The reader will gain a better understanding of the direction nature and culture
+    is heading today by learning how connections were made in the past. It omits that
+    which Raymond Williams called "a working landscape" -- the most intimate human
+    relationship to nature which is people who live and work on it.
+- source_sentence: Why is it recommended to contact a wedding agency or consultant
+    before making a decision
+  sentences:
+  - Perhaps owing to this humiliation I resigned as Chief Winery Warlord, and took
+    a position elsewhere. Following my resignation, we rebooked our date with axe
+    throwing destiny, and converted the night from a team building exercise to a majestic
+    send off in honour of my 10ish glorious years at Coffin Ridge. We arrived in our
+    most impeccable vestments.
+  - Therefore, those private companies increased their own rate of cash burn since
+    the financial markets were willing to fund money-losing enterprises without hesitation.
+    Out of the 100 largest North American-based technology companies, 16 have lost
+    money over the past year.
+  - Yet , it is best to contact a wedding agency or consultant before you make your
+    concluding decision. This will make certain you are dealing with a respectable
+    company.
+- source_sentence: What is the Electronic Music Education and Preservation Project
+    (EMEAPP) and what are its functions
+  sentences:
+  - The Electronic Music Education and Preservation Project (EMEAPP) is the steward
+    of a privately held world-class curated collection of rare vintage electronic
+    instruments and stage-used gear. This includes effects units, amps, organs, synthesizers,
+    electro-mechanical instruments, guitars, prototypes, vintage audio/video media
+    and analog studio gear. In addition, EMEAPP itself is cultivating its own humble
+    collection. It is our charge to cultivate and reap excellent knowledge from these
+    unique resources and return it to our members and the world. We do this as a learning
+    center, through research projects, creative endeavors, media programming and tours,
+    enlightening many people along the way. There is so much to be harvested from
+    history; EMEAPP has a key to the vault. EMEAPP is a private museum, a critical
+    learning center and a multi-media production studio nicely packed into a brick-and-mortar
+    facility outside of Philadelphia, Pennsylvania. EMEAPP is a 501(c)(3) non-profit
+    organization.
+  - You got a problem? Yo, she'll splode it.
+  - I love sex; I think sex is completely absurdly demonized in our culture. But in
+    the end, however much sex you want to have, with however many people in how many
+    ways, to be loved and to love is what human beings really want.
+- source_sentence: What year did the Duchess die and where did it happen
+  sentences:
+  - 'League One
+
+
+    League table
+
+
+    Results summary
+
+
+    Results by matchday
+
+
+    Matches
+
+    On 21 June 2018, the League One fixtures for the forthcoming season were announced.
+    FA Cup
+
+
+    The first round draw was made live on BBC by Dennis Wise and Dion Dublin on 22
+    October.'
+  - "The Duchess was widowed in 2007 and died in London in 2011. Issue \n\nThe Duke\
+    \ and Duchess of Buccleuch and Queensberry had four children:\nRichard Scott,\
+    \ 10th Duke of Buccleuch (b. 1954), married Lady Elizabeth Kerr, daughter of the\
+    \ Marquess of Lothian, and has issue two sons and two daughters. Lord John (born\
+    \ 9 August 1957), married Berrin Torolsan, and lives in Istanbul, Turkey. Lady\
+    \ Charlotte-Anne (born 9 January 1966), married Count Bernard de Castellane in\
+    \ 1991, and has issue two sons and a daughter. Lord Damian (born 8 October 1969),\
+    \ married Elizabeth Powis, and has issue. External links\nJane in her wedding\
+    \ dress  \nMovie clip of Jane's wedding\n\nReferences \n\n1929 births\n2011 deaths\n\
+    British duchesses by marriage\nJane\nScottish female models\nBritish cookbook\
+    \ writers\nWomen cookbook writers"
+  - Is this common, do other people with epilepsy have dangerously low appetites?
+    So we left there and stopped and got her a bite to eat.
+- source_sentence: Why is it important to keep moving over the summer
+  sentences:
+  - It's important to keep moving over the summer!
+  - '2008. CHENG HF, LEE YM, Chu CH, Leung WK & Mok TMY. - Journal Editor (Hong Kong
+    Medical Journal) 2008
+
+    - Editor-in-Chief (Hong Kong Dental Journal) 2007
+
+    - Editor-in-Chief (Hong Kong Dental Journal) 2006
+
+    - Deputy Editor (Hong Kong Dental Journal) 2004'
+  - Both demand collective action and shared resources. While one is distinctly egalitarian
+    and the other hierarchical in nature, both speak of sublimating private goals
+    for the achievement of larger, shared ones.
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# SentenceTransformer based on Snowflake/snowflake-arctic-embed-l-v2.0
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Snowflake/snowflake-arctic-embed-l-v2.0](https://huggingface.co/Snowflake/snowflake-arctic-embed-l-v2.0). It maps sentences & paragraphs to a 1024-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:** [Snowflake/snowflake-arctic-embed-l-v2.0](https://huggingface.co/Snowflake/snowflake-arctic-embed-l-v2.0) <!-- at revision 7f311bb640ad3babc0a4e3a8873240dcba44c9d2 -->
+- **Maximum Sequence Length:** 1024 tokens
+- **Output Dimensionality:** 1024 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': 1024, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
+  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, '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("Jrinky/snowflake")
+# Run inference
+sentences = [
+    'Why is it important to keep moving over the summer',
+    "It's important to keep moving over the summer!",
+    '2008. CHENG HF, LEE YM, Chu CH, Leung WK & Mok TMY. - Journal Editor (Hong Kong Medical Journal) 2008\n- Editor-in-Chief (Hong Kong Dental Journal) 2007\n- Editor-in-Chief (Hong Kong Dental Journal) 2006\n- Deputy Editor (Hong Kong Dental Journal) 2004',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 1024]
+
+# 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: 69,500 training samples
+* Columns: <code>anchor</code> and <code>positive</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                            | positive                                                                             |
+  |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
+  | type    | string                                                                            | string                                                                               |
+  | details | <ul><li>min: 6 tokens</li><li>mean: 17.47 tokens</li><li>max: 44 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 113.33 tokens</li><li>max: 1024 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                     | positive                                                                                                                                                                                                                                                                           |
+  |:-----------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>What might have been unnecessary if better emergency plans had been implemented</code>               | <code>If better emergency plans had been in place, maybe chemical dipersants wouldn't be needed. And on and on.</code>                                                                                                                                                             |
+  | <code>What was the year of publication for the 3rd Edition of 'Regular Polytopes' by H.S.M. Coxeter</code> | <code>Coxeter, Regular Polytopes, 3rd Edition, Dover New York, 1973 <br> Kaleidoscopes: Selected Writings of H.S.M. Coxeter, edited by F. Arthur Sherk, Peter McMullen, Anthony C. Thompson, Asia Ivic Weiss, Wiley-Interscience Publication, 1995,  <br> (Paper 22) H.S.M.</code> |
+  | <code>Who is the author of the GURPS Shapeshifters supplement</code>                                       | <code>GURPS Shapeshifters () is a supplement by Robert M. Schroeck for the GURPS role-playing game system, third edition.</code>                                                                                                                                                   |
+* Loss: <code>selfloss.Infonce</code> with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Evaluation Dataset
+
+#### Unnamed Dataset
+
+
+* Size: 17,376 evaluation samples
+* Columns: <code>anchor</code> and <code>positive</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                            | positive                                                                             |
+  |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
+  | type    | string                                                                            | string                                                                               |
+  | details | <ul><li>min: 6 tokens</li><li>mean: 16.87 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 115.36 tokens</li><li>max: 1024 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                         | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
+  |:---------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>What impressive achievements did the Warriors accomplish during their last season in Division III</code> | <code>The Warriors were among the most lethal offensive teams in Division III this past year, posting a team batting average of .344 and averaging nearly seven runs per game, smacking 29 home runs, and collecting nearly 600 total bases. They shared the Little East Conference regular-season championship and later knocked off the top seed in the NCAA regional tournament (Montclair State) en route to their winningest season in 14 years.</code> |
+  | <code>How many bars had nectar and capped honey on them</code>                                                 | <code>Eight of the bars had nectar and capped honey on them. There are eighteen bars with brood in some form on them and a mix of workers and drones.</code>                                                                                                                                                                                                                                                                                                 |
+  | <code>What idea is being requested regarding the 'triangle'</code>                                             | <code>Next up...the "triangle". Please, seriously, if anyone could float me an idea, I would really appreciate it.</code>                                                                                                                                                                                                                                                                                                                                    |
+* Loss: <code>selfloss.Infonce</code> with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 3
+- `per_device_eval_batch_size`: 3
+- `learning_rate`: 5e-06
+- `num_train_epochs`: 5
+- `warmup_ratio`: 0.1
+- `fp16`: True
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 3
+- `per_device_eval_batch_size`: 3
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 5e-06
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 5
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `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`: True
+- `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`: True
+- `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
+- `eval_on_start`: False
+- `eval_use_gather_object`: False
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | Validation Loss |
+|:------:|:----:|:-------------:|:---------------:|
+| 0.0777 | 150  | 0.0257        | 0.0134          |
+| 0.1554 | 300  | 0.0136        | 0.0082          |
+| 0.2332 | 450  | 0.0079        | 0.0062          |
+| 0.3109 | 600  | 0.0065        | 0.0051          |
+| 0.3886 | 750  | 0.0059        | 0.0045          |
+| 0.4663 | 900  | 0.0057        | 0.0040          |
+| 0.5440 | 1050 | 0.0064        | 0.0037          |
+| 0.6218 | 1200 | 0.005         | 0.0034          |
+| 0.6995 | 1350 | 0.0052        | 0.0034          |
+| 0.7772 | 1500 | 0.0041        | 0.0032          |
+
+
+### Framework Versions
+- Python: 3.12.3
+- Sentence Transformers: 3.2.0
+- Transformers: 4.44.2
+- PyTorch: 2.6.0+cu124
+- Accelerate: 1.3.0
+- Datasets: 2.19.0
+- 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",
+}
+```
+
+#### Infonce
+```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 +1,28 @@
+{
+  "_name_or_path": "/root/autodl-tmp/work_dir/models/snowflake-arctic-embed-l-v2.0-selfloss/checkpoint-1500",
+  "architectures": [
+    "XLMRobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 8194,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

config_sentence_transformers.json

@@ -0,0 +1,12 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.2.0",
+    "transformers": "4.44.2",
+    "pytorch": "2.6.0+cu124"
+  },
+  "prompts": {
+    "query": "query: "
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": null
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c7800583766c01c099fbd028593959fbf0032a6c9e1b164a6a54389fda3d8da
+size 2271064456

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": 1024,
+  "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
+  },
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6e3b8957de04e3a4ed42b1a11381556f9adad8d0d502b9dd071c75f626b28f40
+size 17083053

tokenizer_config.json

@@ -0,0 +1,61 @@
+{
+  "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
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 512,
+  "model_max_length": 1024,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}