Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
dense
Generated from Trainer
dataset_size:5920
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use HariishHafiiz/sbert-bug-eclipse-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HariishHafiiz/sbert-bug-eclipse-ft with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HariishHafiiz/sbert-bug-eclipse-ft") sentences = [ "debugger not reusing a ireusableeditor eclipse . doubleclick a source file of my language. an editor is opened with a fileeditorinput for it. well call it instance. debug the program file of my language. i have my own mylanguageinput for a runtime program so that i can do coloring based on vm states see bug the debugger will not reuse the already open ireusableeditor that i have setting its input object was what i expected. it will choose to open a new editor instead. well call this instance. debug more instances of the same program. now the debugger will reuse instance. why cant the debugger reuse instance from the beginning note that this problem was hit by a workaround for bug", "would like to say what text attributes to use when selecting the executing statement for my language id like to have the currently executing line colored depending on state from my vm. id imagine that passing such text attributes when generating these debug events would be one way to go. note that is is a spinoff from bug", "ant builds using an external jvm with input tasks cannot request input. please ensure that an inputhandler is being provided for external ant tasks currently the ant will request the input from stdin which is not possible on the current console rather than popping up an appropriate dialog as it would when run from within the eclipse vm.", "workbench startup is throwing dialog rather than logging to .log took new startedt on old workspace got annternal error dialog executable extension definition for class not found. hit ok t came up ok nothingn log" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Add new SentenceTransformer model.
Browse files- 1_Pooling/config.json +10 -0
- README.md +92 -0
- config.json +24 -0
- config_sentence_transformers.json +9 -0
- model.safetensors +3 -0
- modules.json +20 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +72 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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README.md
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---
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library_name: sentence-transformers
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pipeline_tag: sentence-similarity
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tags:
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- sentence-transformers
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- feature-extraction
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- sentence-similarity
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---
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# HariishHafiiz/sbert-bug-eclipse-ft
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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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## Usage (Sentence-Transformers)
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Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
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```
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pip install -U sentence-transformers
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```
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Then you can use the model like this:
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```python
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from sentence_transformers import SentenceTransformer
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sentences = ["This is an example sentence", "Each sentence is converted"]
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model = SentenceTransformer('HariishHafiiz/sbert-bug-eclipse-ft')
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embeddings = model.encode(sentences)
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print(embeddings)
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```
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## Evaluation Results
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<!--- Describe how your model was evaluated -->
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For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=HariishHafiiz/sbert-bug-eclipse-ft)
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## Training
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The model was trained with the parameters:
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**DataLoader**:
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`torch.utils.data.dataloader.DataLoader` of length 740 with parameters:
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```
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{'batch_size': 8, '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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`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters:
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```
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{'scale': 20.0, 'similarity_fct': 'cos_sim'}
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```
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Parameters of the fit()-Method:
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```
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{
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"epochs": 3,
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"evaluation_steps": 0,
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"evaluator": "NoneType",
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"max_grad_norm": 1,
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"optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
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"optimizer_params": {
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"lr": 2e-05
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},
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"scheduler": "WarmupLinear",
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"steps_per_epoch": null,
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"warmup_steps": 100,
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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': 256, '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, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
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(2): Normalize()
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)
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```
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## Citing & Authors
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<!--- Describe where people can find more information -->
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config.json
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{
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"_name_or_path": "sentence-transformers/all-mpnet-base-v2",
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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": "4.38.2",
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"vocab_size": 30527
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}
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config_sentence_transformers.json
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{
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"__version__": {
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"sentence_transformers": "2.0.0",
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"transformers": "4.6.1",
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"pytorch": "1.8.1"
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},
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"prompts": {},
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"default_prompt_name": null
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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 sha256:24ed16aab11ad8cf9a4bcea6a847d5879947a27eb35d22beed19386bb616ab2d
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size 437967672
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modules.json
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[
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{
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"idx": 0,
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"name": "0",
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"path": "",
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"type": "sentence_transformers.models.Transformer"
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},
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{
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"idx": 1,
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"name": "1",
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"path": "1_Pooling",
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"type": "sentence_transformers.models.Pooling"
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},
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{
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"idx": 2,
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"name": "2",
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"path": "2_Normalize",
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"type": "sentence_transformers.models.Normalize"
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}
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]
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sentence_bert_config.json
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{
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"max_seq_length": 256,
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"do_lower_case": false
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}
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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| 7 |
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"single_word": false
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| 8 |
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},
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"cls_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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| 19 |
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"normalized": false,
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"rstrip": false,
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| 21 |
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"single_word": false
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},
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"mask_token": {
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| 24 |
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"content": "<mask>",
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| 25 |
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"lstrip": true,
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| 26 |
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"normalized": false,
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| 27 |
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"rstrip": false,
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| 28 |
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"single_word": false
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| 29 |
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},
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| 30 |
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"pad_token": {
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| 31 |
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"content": "<pad>",
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| 32 |
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"lstrip": false,
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| 33 |
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"normalized": false,
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| 34 |
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"rstrip": false,
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| 35 |
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"single_word": false
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| 36 |
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},
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| 37 |
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"sep_token": {
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| 38 |
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"content": "</s>",
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| 39 |
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"lstrip": false,
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| 40 |
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"normalized": false,
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| 41 |
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"rstrip": false,
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| 42 |
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"single_word": false
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| 43 |
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},
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| 44 |
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"unk_token": {
|
| 45 |
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"content": "[UNK]",
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| 46 |
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"lstrip": false,
|
| 47 |
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"normalized": false,
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| 48 |
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"rstrip": false,
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| 49 |
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"single_word": false
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| 50 |
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}
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| 51 |
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}
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tokenizer.json
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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| 7 |
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"rstrip": false,
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"single_word": false,
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| 9 |
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"special": true
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},
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| 11 |
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"1": {
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| 12 |
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"content": "<pad>",
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| 13 |
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"lstrip": false,
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| 14 |
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"normalized": false,
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| 15 |
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"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"2": {
|
| 20 |
+
"content": "</s>",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"3": {
|
| 28 |
+
"content": "<unk>",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": true,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
},
|
| 35 |
+
"104": {
|
| 36 |
+
"content": "[UNK]",
|
| 37 |
+
"lstrip": false,
|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": true
|
| 42 |
+
},
|
| 43 |
+
"30526": {
|
| 44 |
+
"content": "<mask>",
|
| 45 |
+
"lstrip": true,
|
| 46 |
+
"normalized": false,
|
| 47 |
+
"rstrip": false,
|
| 48 |
+
"single_word": false,
|
| 49 |
+
"special": true
|
| 50 |
+
}
|
| 51 |
+
},
|
| 52 |
+
"bos_token": "<s>",
|
| 53 |
+
"clean_up_tokenization_spaces": true,
|
| 54 |
+
"cls_token": "<s>",
|
| 55 |
+
"do_lower_case": true,
|
| 56 |
+
"eos_token": "</s>",
|
| 57 |
+
"mask_token": "<mask>",
|
| 58 |
+
"max_length": 128,
|
| 59 |
+
"model_max_length": 512,
|
| 60 |
+
"pad_to_multiple_of": null,
|
| 61 |
+
"pad_token": "<pad>",
|
| 62 |
+
"pad_token_type_id": 0,
|
| 63 |
+
"padding_side": "right",
|
| 64 |
+
"sep_token": "</s>",
|
| 65 |
+
"stride": 0,
|
| 66 |
+
"strip_accents": null,
|
| 67 |
+
"tokenize_chinese_chars": true,
|
| 68 |
+
"tokenizer_class": "MPNetTokenizer",
|
| 69 |
+
"truncation_side": "right",
|
| 70 |
+
"truncation_strategy": "longest_first",
|
| 71 |
+
"unk_token": "[UNK]"
|
| 72 |
+
}
|
vocab.txt
ADDED
|
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|
|