Catchy1282
commited on
Commit
•
5e06e74
1
Parent(s):
550b50f
Push model using huggingface_hub.
Browse files- 1_Pooling/config.json +10 -0
- README.md +131 -0
- config.json +24 -0
- config_sentence_transformers.json +10 -0
- config_setfit.json +4 -0
- model.safetensors +3 -0
- model_head.pkl +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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base_model: sentence-transformers/all-mpnet-base-v2
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library_name: setfit
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metrics:
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- accuracy
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pipeline_tag: text-classification
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tags:
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- setfit
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- sentence-transformers
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- text-classification
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- generated_from_setfit_trainer
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widget: []
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inference: true
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---
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# SetFit with sentence-transformers/all-mpnet-base-v2
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This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) as the Sentence Transformer embedding model. A GradientBoostingClassifier instance is used for classification.
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The model has been trained using an efficient few-shot learning technique that involves:
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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2. Training a classification head with features from the fine-tuned Sentence Transformer.
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## Model Details
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### Model Description
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- **Model Type:** SetFit
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- **Sentence Transformer body:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2)
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- **Classification head:** a GradientBoostingClassifier instance
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- **Maximum Sequence Length:** 384 tokens
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<!-- - **Number of Classes:** Unknown -->
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Model Sources
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- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
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- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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## Uses
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### Direct Use for Inference
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First install the SetFit library:
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```bash
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pip install setfit
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```
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Then you can load this model and run inference.
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```python
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from setfit import SetFitModel
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# Download from the 🤗 Hub
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model = SetFitModel.from_pretrained("Catchy1282/GradientBoosting_model_5_samples_per_label")
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# Run inference
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preds = model("I loved the spiderman movie!")
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```
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<!--
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### Downstream Use
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*List how someone could finetune this model on their own dataset.*
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-->
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<!--
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### Out-of-Scope Use
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*List how the model may foreseeably be misused and address what users ought not to do with the model.*
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-->
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<!--
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## Bias, Risks and Limitations
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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-->
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<!--
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### Recommendations
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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-->
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## Training Details
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### Framework Versions
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- Python: 3.11.9
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- SetFit: 1.0.3
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- Sentence Transformers: 3.0.1
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- Transformers: 4.39.0
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- PyTorch: 2.3.0+cu121
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- Datasets: 2.20.0
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- Tokenizers: 0.15.2
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## Citation
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### BibTeX
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```bibtex
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@article{https://doi.org/10.48550/arxiv.2209.11055,
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doi = {10.48550/ARXIV.2209.11055},
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url = {https://arxiv.org/abs/2209.11055},
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author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
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keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
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title = {Efficient Few-Shot Learning Without Prompts},
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publisher = {arXiv},
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year = {2022},
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copyright = {Creative Commons Attribution 4.0 International}
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}
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```
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<!--
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## Glossary
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*Clearly define terms in order to be accessible across audiences.*
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-->
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<!--
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## Model Card Authors
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*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
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-->
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<!--
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## Model Card Contact
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*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
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-->
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config.json
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{
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"_name_or_path": "./RandonForest_model_5_samples_per_label",
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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": "4.39.0",
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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": "3.0.1",
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"transformers": "4.39.0",
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"pytorch": "2.3.0+cu121"
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},
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"prompts": {},
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"default_prompt_name": null,
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"similarity_fn_name": null
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}
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config_setfit.json
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{
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"normalize_embeddings": false,
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"labels": 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 sha256:5664c17154a48a8becb67f9761075efa7a63b1b7defeed7f52bedd7bf6953fa6
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size 437967672
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model_head.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:922211c1a1d2124a71b19d1ee77507e6b14f08b97b1ffc9ec577ba847b5ca41d
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size 209101
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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": 384,
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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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"single_word": false
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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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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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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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"pad_token": {
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"content": "<pad>",
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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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"sep_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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"unk_token": {
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"content": "[UNK]",
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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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}
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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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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<pad>",
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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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"special": true
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},
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"2": {
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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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"special": true
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},
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"3": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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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": 384,
|
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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|
|