VityaVitalich
commited on
Commit
•
066931b
1
Parent(s):
ea80da8
Upload tokenizer
Browse files- README.md +199 -0
- added_tokens.json +126 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +163 -0
- tokenizer_config.json +1167 -0
- vocab.json +0 -0
README.md
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---
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library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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added_tokens.json
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{
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"__af__": 256001,
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"__am__": 256002,
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"__ar__": 256003,
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"__as__": 256004,
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"__ast__": 256005,
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"__ay__": 256006,
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"__az__": 256007,
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"__ba__": 256008,
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"__be__": 256009,
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"__bg__": 256010,
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"__bn__": 256011,
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"__br__": 256012,
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"__bs__": 256013,
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"__ca__": 256014,
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"__ceb__": 256015,
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"__cjk__": 256016,
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"__cs__": 256017,
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"__cy__": 256018,
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"__da__": 256019,
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"__de__": 256020,
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"__dyu__": 256021,
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"__el__": 256022,
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"__en__": 256023,
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"__es__": 256024,
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"__et__": 256025,
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"__fa__": 256026,
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"__ff__": 256027,
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"__fi__": 256028,
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"__fr__": 256029,
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"__fy__": 256030,
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"__ga__": 256031,
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"__gd__": 256032,
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"__gl__": 256033,
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"__gu__": 256034,
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"__ha__": 256035,
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"__he__": 256036,
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"__hi__": 256037,
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"__hr__": 256038,
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"__ht__": 256039,
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"__hu__": 256040,
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"__hy__": 256041,
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"__id__": 256042,
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"__ig__": 256043,
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"__ilo__": 256044,
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"__is__": 256045,
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"__it__": 256046,
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"__ja__": 256047,
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"__jv__": 256048,
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"__ka__": 256049,
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"__kac__": 256050,
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"__kam__": 256051,
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"__kea__": 256052,
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"__kg__": 256053,
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"__kk__": 256054,
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"__km__": 256055,
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"__kmb__": 256056,
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"__kmr__": 256057,
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"__kn__": 256058,
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"__ko__": 256059,
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"__ku__": 256060,
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"__ky__": 256061,
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"__lb__": 256062,
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"__lg__": 256063,
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"__ln__": 256064,
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"__lo__": 256065,
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"__lt__": 256066,
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"__luo__": 256067,
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"__lv__": 256068,
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"__mg__": 256069,
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"__mi__": 256070,
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"__mk__": 256071,
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"__ml__": 256072,
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"__mn__": 256073,
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"__mr__": 256074,
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"__ms__": 256075,
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"__mt__": 256076,
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"__my__": 256077,
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"__ne__": 256078,
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"__nl__": 256079,
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"__no__": 256080,
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"__ns__": 256081,
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"__ny__": 256082,
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"__oc__": 256083,
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"__om__": 256084,
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"__or__": 256085,
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"__pa__": 256086,
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"__pl__": 256087,
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"__ps__": 256088,
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"__pt__": 256089,
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"__qu__": 256090,
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"__ro__": 256091,
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"__ru__": 256092,
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"__sd__": 256093,
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"__shn__": 256094,
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"__si__": 256095,
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"__sk__": 256096,
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"__sl__": 256097,
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"__sn__": 256098,
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"__so__": 256099,
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"__sq__": 256100,
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"__sr__": 256101,
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"__ss__": 256102,
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"__su__": 256103,
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"__sv__": 256104,
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"__sw__": 256105,
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"__ta__": 256106,
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"__te__": 256107,
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"__tg__": 256108,
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"__th__": 256109,
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"__ti__": 256110,
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"__tl__": 256111,
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"__tn__": 256112,
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"__tr__": 256113,
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"__uk__": 256114,
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"__umb__": 256115,
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"__ur__": 256116,
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"__uz__": 256117,
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"__vi__": 256118,
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"__wo__": 256119,
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"__xh__": 256120,
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"__yi__": 256121,
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"__yo__": 256122,
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"__zh__": 256123,
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"__zu__": 256124
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}
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:6ee4dc054a17c18fe81f76c0b1cda00e9fc1cfd9e0f1a16cb6d77009e2076653
|
3 |
+
size 4870365
|
special_tokens_map.json
ADDED
@@ -0,0 +1,163 @@
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1 |
+
{
|
2 |
+
"additional_special_tokens": [
|
3 |
+
"__af__",
|
4 |
+
"__am__",
|
5 |
+
"__ar__",
|
6 |
+
"__as__",
|
7 |
+
"__ast__",
|
8 |
+
"__ay__",
|
9 |
+
"__az__",
|
10 |
+
"__ba__",
|
11 |
+
"__be__",
|
12 |
+
"__bg__",
|
13 |
+
"__bn__",
|
14 |
+
"__br__",
|
15 |
+
"__bs__",
|
16 |
+
"__ca__",
|
17 |
+
"__ceb__",
|
18 |
+
"__cjk__",
|
19 |
+
"__cs__",
|
20 |
+
"__cy__",
|
21 |
+
"__da__",
|
22 |
+
"__de__",
|
23 |
+
"__dyu__",
|
24 |
+
"__el__",
|
25 |
+
"__en__",
|
26 |
+
"__es__",
|
27 |
+
"__et__",
|
28 |
+
"__fa__",
|
29 |
+
"__ff__",
|
30 |
+
"__fi__",
|
31 |
+
"__fr__",
|
32 |
+
"__fy__",
|
33 |
+
"__ga__",
|
34 |
+
"__gd__",
|
35 |
+
"__gl__",
|
36 |
+
"__gu__",
|
37 |
+
"__ha__",
|
38 |
+
"__he__",
|
39 |
+
"__hi__",
|
40 |
+
"__hr__",
|
41 |
+
"__ht__",
|
42 |
+
"__hu__",
|
43 |
+
"__hy__",
|
44 |
+
"__id__",
|
45 |
+
"__ig__",
|
46 |
+
"__ilo__",
|
47 |
+
"__is__",
|
48 |
+
"__it__",
|
49 |
+
"__ja__",
|
50 |
+
"__jv__",
|
51 |
+
"__ka__",
|
52 |
+
"__kac__",
|
53 |
+
"__kam__",
|
54 |
+
"__kea__",
|
55 |
+
"__kg__",
|
56 |
+
"__kk__",
|
57 |
+
"__km__",
|
58 |
+
"__kmb__",
|
59 |
+
"__kmr__",
|
60 |
+
"__kn__",
|
61 |
+
"__ko__",
|
62 |
+
"__ku__",
|
63 |
+
"__ky__",
|
64 |
+
"__lb__",
|
65 |
+
"__lg__",
|
66 |
+
"__ln__",
|
67 |
+
"__lo__",
|
68 |
+
"__lt__",
|
69 |
+
"__luo__",
|
70 |
+
"__lv__",
|
71 |
+
"__mg__",
|
72 |
+
"__mi__",
|
73 |
+
"__mk__",
|
74 |
+
"__ml__",
|
75 |
+
"__mn__",
|
76 |
+
"__mr__",
|
77 |
+
"__ms__",
|
78 |
+
"__mt__",
|
79 |
+
"__my__",
|
80 |
+
"__ne__",
|
81 |
+
"__nl__",
|
82 |
+
"__no__",
|
83 |
+
"__ns__",
|
84 |
+
"__ny__",
|
85 |
+
"__oc__",
|
86 |
+
"__om__",
|
87 |
+
"__or__",
|
88 |
+
"__pa__",
|
89 |
+
"__pl__",
|
90 |
+
"__ps__",
|
91 |
+
"__pt__",
|
92 |
+
"__qu__",
|
93 |
+
"__ro__",
|
94 |
+
"__ru__",
|
95 |
+
"__sd__",
|
96 |
+
"__shn__",
|
97 |
+
"__si__",
|
98 |
+
"__sk__",
|
99 |
+
"__sl__",
|
100 |
+
"__sn__",
|
101 |
+
"__so__",
|
102 |
+
"__sq__",
|
103 |
+
"__sr__",
|
104 |
+
"__ss__",
|
105 |
+
"__su__",
|
106 |
+
"__sv__",
|
107 |
+
"__sw__",
|
108 |
+
"__ta__",
|
109 |
+
"__te__",
|
110 |
+
"__tg__",
|
111 |
+
"__th__",
|
112 |
+
"__ti__",
|
113 |
+
"__tl__",
|
114 |
+
"__tn__",
|
115 |
+
"__tr__",
|
116 |
+
"__uk__",
|
117 |
+
"__umb__",
|
118 |
+
"__ur__",
|
119 |
+
"__uz__",
|
120 |
+
"__vi__",
|
121 |
+
"__wo__",
|
122 |
+
"__xh__",
|
123 |
+
"__yi__",
|
124 |
+
"__yo__",
|
125 |
+
"__zh__",
|
126 |
+
"__zu__"
|
127 |
+
],
|
128 |
+
"bos_token": {
|
129 |
+
"content": "<s>",
|
130 |
+
"lstrip": false,
|
131 |
+
"normalized": false,
|
132 |
+
"rstrip": false,
|
133 |
+
"single_word": false
|
134 |
+
},
|
135 |
+
"eos_token": {
|
136 |
+
"content": "</s>",
|
137 |
+
"lstrip": false,
|
138 |
+
"normalized": false,
|
139 |
+
"rstrip": false,
|
140 |
+
"single_word": false
|
141 |
+
},
|
142 |
+
"pad_token": {
|
143 |
+
"content": "<pad>",
|
144 |
+
"lstrip": false,
|
145 |
+
"normalized": false,
|
146 |
+
"rstrip": false,
|
147 |
+
"single_word": false
|
148 |
+
},
|
149 |
+
"sep_token": {
|
150 |
+
"content": "</s>",
|
151 |
+
"lstrip": false,
|
152 |
+
"normalized": false,
|
153 |
+
"rstrip": false,
|
154 |
+
"single_word": false
|
155 |
+
},
|
156 |
+
"unk_token": {
|
157 |
+
"content": "<unk>",
|
158 |
+
"lstrip": false,
|
159 |
+
"normalized": false,
|
160 |
+
"rstrip": false,
|
161 |
+
"single_word": false
|
162 |
+
}
|
163 |
+
}
|
tokenizer_config.json
ADDED
@@ -0,0 +1,1167 @@
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1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
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"0": {
|
4 |
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5 |
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6 |
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7 |
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8 |
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9 |
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10 |
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11 |
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12 |
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13 |
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14 |
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15 |
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16 |
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17 |
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18 |
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},
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19 |
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|
20 |
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21 |
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22 |
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23 |
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24 |
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25 |
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26 |
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},
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27 |
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|
28 |
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29 |
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30 |
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31 |
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32 |
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33 |
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34 |
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35 |
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|
36 |
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37 |
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38 |
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39 |
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40 |
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|
41 |
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42 |
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|
43 |
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|
44 |
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45 |
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46 |
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47 |
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48 |
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49 |
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50 |
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51 |
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52 |
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53 |
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54 |
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57 |
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58 |
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59 |
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60 |
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64 |
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65 |
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66 |
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68 |
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70 |
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74 |
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76 |
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78 |
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80 |
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82 |
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83 |
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84 |
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85 |
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86 |
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88 |
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90 |
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92 |
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104 |
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106 |
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107 |
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108 |
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109 |
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110 |
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114 |
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116 |
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124 |
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125 |
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126 |
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130 |
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132 |
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146 |
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148 |
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154 |
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156 |
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158 |
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162 |
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164 |
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165 |
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166 |
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170 |
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172 |
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173 |
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174 |
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178 |
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179 |
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180 |
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188 |
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210 |
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212 |
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213 |
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214 |
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216 |
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220 |
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230 |
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236 |
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238 |
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"content": "__shn__",
|
781 |
+
"lstrip": false,
|
782 |
+
"normalized": false,
|
783 |
+
"rstrip": false,
|
784 |
+
"single_word": false,
|
785 |
+
"special": true
|
786 |
+
},
|
787 |
+
"256095": {
|
788 |
+
"content": "__si__",
|
789 |
+
"lstrip": false,
|
790 |
+
"normalized": false,
|
791 |
+
"rstrip": false,
|
792 |
+
"single_word": false,
|
793 |
+
"special": true
|
794 |
+
},
|
795 |
+
"256096": {
|
796 |
+
"content": "__sk__",
|
797 |
+
"lstrip": false,
|
798 |
+
"normalized": false,
|
799 |
+
"rstrip": false,
|
800 |
+
"single_word": false,
|
801 |
+
"special": true
|
802 |
+
},
|
803 |
+
"256097": {
|
804 |
+
"content": "__sl__",
|
805 |
+
"lstrip": false,
|
806 |
+
"normalized": false,
|
807 |
+
"rstrip": false,
|
808 |
+
"single_word": false,
|
809 |
+
"special": true
|
810 |
+
},
|
811 |
+
"256098": {
|
812 |
+
"content": "__sn__",
|
813 |
+
"lstrip": false,
|
814 |
+
"normalized": false,
|
815 |
+
"rstrip": false,
|
816 |
+
"single_word": false,
|
817 |
+
"special": true
|
818 |
+
},
|
819 |
+
"256099": {
|
820 |
+
"content": "__so__",
|
821 |
+
"lstrip": false,
|
822 |
+
"normalized": false,
|
823 |
+
"rstrip": false,
|
824 |
+
"single_word": false,
|
825 |
+
"special": true
|
826 |
+
},
|
827 |
+
"256100": {
|
828 |
+
"content": "__sq__",
|
829 |
+
"lstrip": false,
|
830 |
+
"normalized": false,
|
831 |
+
"rstrip": false,
|
832 |
+
"single_word": false,
|
833 |
+
"special": true
|
834 |
+
},
|
835 |
+
"256101": {
|
836 |
+
"content": "__sr__",
|
837 |
+
"lstrip": false,
|
838 |
+
"normalized": false,
|
839 |
+
"rstrip": false,
|
840 |
+
"single_word": false,
|
841 |
+
"special": true
|
842 |
+
},
|
843 |
+
"256102": {
|
844 |
+
"content": "__ss__",
|
845 |
+
"lstrip": false,
|
846 |
+
"normalized": false,
|
847 |
+
"rstrip": false,
|
848 |
+
"single_word": false,
|
849 |
+
"special": true
|
850 |
+
},
|
851 |
+
"256103": {
|
852 |
+
"content": "__su__",
|
853 |
+
"lstrip": false,
|
854 |
+
"normalized": false,
|
855 |
+
"rstrip": false,
|
856 |
+
"single_word": false,
|
857 |
+
"special": true
|
858 |
+
},
|
859 |
+
"256104": {
|
860 |
+
"content": "__sv__",
|
861 |
+
"lstrip": false,
|
862 |
+
"normalized": false,
|
863 |
+
"rstrip": false,
|
864 |
+
"single_word": false,
|
865 |
+
"special": true
|
866 |
+
},
|
867 |
+
"256105": {
|
868 |
+
"content": "__sw__",
|
869 |
+
"lstrip": false,
|
870 |
+
"normalized": false,
|
871 |
+
"rstrip": false,
|
872 |
+
"single_word": false,
|
873 |
+
"special": true
|
874 |
+
},
|
875 |
+
"256106": {
|
876 |
+
"content": "__ta__",
|
877 |
+
"lstrip": false,
|
878 |
+
"normalized": false,
|
879 |
+
"rstrip": false,
|
880 |
+
"single_word": false,
|
881 |
+
"special": true
|
882 |
+
},
|
883 |
+
"256107": {
|
884 |
+
"content": "__te__",
|
885 |
+
"lstrip": false,
|
886 |
+
"normalized": false,
|
887 |
+
"rstrip": false,
|
888 |
+
"single_word": false,
|
889 |
+
"special": true
|
890 |
+
},
|
891 |
+
"256108": {
|
892 |
+
"content": "__tg__",
|
893 |
+
"lstrip": false,
|
894 |
+
"normalized": false,
|
895 |
+
"rstrip": false,
|
896 |
+
"single_word": false,
|
897 |
+
"special": true
|
898 |
+
},
|
899 |
+
"256109": {
|
900 |
+
"content": "__th__",
|
901 |
+
"lstrip": false,
|
902 |
+
"normalized": false,
|
903 |
+
"rstrip": false,
|
904 |
+
"single_word": false,
|
905 |
+
"special": true
|
906 |
+
},
|
907 |
+
"256110": {
|
908 |
+
"content": "__ti__",
|
909 |
+
"lstrip": false,
|
910 |
+
"normalized": false,
|
911 |
+
"rstrip": false,
|
912 |
+
"single_word": false,
|
913 |
+
"special": true
|
914 |
+
},
|
915 |
+
"256111": {
|
916 |
+
"content": "__tl__",
|
917 |
+
"lstrip": false,
|
918 |
+
"normalized": false,
|
919 |
+
"rstrip": false,
|
920 |
+
"single_word": false,
|
921 |
+
"special": true
|
922 |
+
},
|
923 |
+
"256112": {
|
924 |
+
"content": "__tn__",
|
925 |
+
"lstrip": false,
|
926 |
+
"normalized": false,
|
927 |
+
"rstrip": false,
|
928 |
+
"single_word": false,
|
929 |
+
"special": true
|
930 |
+
},
|
931 |
+
"256113": {
|
932 |
+
"content": "__tr__",
|
933 |
+
"lstrip": false,
|
934 |
+
"normalized": false,
|
935 |
+
"rstrip": false,
|
936 |
+
"single_word": false,
|
937 |
+
"special": true
|
938 |
+
},
|
939 |
+
"256114": {
|
940 |
+
"content": "__uk__",
|
941 |
+
"lstrip": false,
|
942 |
+
"normalized": false,
|
943 |
+
"rstrip": false,
|
944 |
+
"single_word": false,
|
945 |
+
"special": true
|
946 |
+
},
|
947 |
+
"256115": {
|
948 |
+
"content": "__umb__",
|
949 |
+
"lstrip": false,
|
950 |
+
"normalized": false,
|
951 |
+
"rstrip": false,
|
952 |
+
"single_word": false,
|
953 |
+
"special": true
|
954 |
+
},
|
955 |
+
"256116": {
|
956 |
+
"content": "__ur__",
|
957 |
+
"lstrip": false,
|
958 |
+
"normalized": false,
|
959 |
+
"rstrip": false,
|
960 |
+
"single_word": false,
|
961 |
+
"special": true
|
962 |
+
},
|
963 |
+
"256117": {
|
964 |
+
"content": "__uz__",
|
965 |
+
"lstrip": false,
|
966 |
+
"normalized": false,
|
967 |
+
"rstrip": false,
|
968 |
+
"single_word": false,
|
969 |
+
"special": true
|
970 |
+
},
|
971 |
+
"256118": {
|
972 |
+
"content": "__vi__",
|
973 |
+
"lstrip": false,
|
974 |
+
"normalized": false,
|
975 |
+
"rstrip": false,
|
976 |
+
"single_word": false,
|
977 |
+
"special": true
|
978 |
+
},
|
979 |
+
"256119": {
|
980 |
+
"content": "__wo__",
|
981 |
+
"lstrip": false,
|
982 |
+
"normalized": false,
|
983 |
+
"rstrip": false,
|
984 |
+
"single_word": false,
|
985 |
+
"special": true
|
986 |
+
},
|
987 |
+
"256120": {
|
988 |
+
"content": "__xh__",
|
989 |
+
"lstrip": false,
|
990 |
+
"normalized": false,
|
991 |
+
"rstrip": false,
|
992 |
+
"single_word": false,
|
993 |
+
"special": true
|
994 |
+
},
|
995 |
+
"256121": {
|
996 |
+
"content": "__yi__",
|
997 |
+
"lstrip": false,
|
998 |
+
"normalized": false,
|
999 |
+
"rstrip": false,
|
1000 |
+
"single_word": false,
|
1001 |
+
"special": true
|
1002 |
+
},
|
1003 |
+
"256122": {
|
1004 |
+
"content": "__yo__",
|
1005 |
+
"lstrip": false,
|
1006 |
+
"normalized": false,
|
1007 |
+
"rstrip": false,
|
1008 |
+
"single_word": false,
|
1009 |
+
"special": true
|
1010 |
+
},
|
1011 |
+
"256123": {
|
1012 |
+
"content": "__zh__",
|
1013 |
+
"lstrip": false,
|
1014 |
+
"normalized": false,
|
1015 |
+
"rstrip": false,
|
1016 |
+
"single_word": false,
|
1017 |
+
"special": true
|
1018 |
+
},
|
1019 |
+
"256124": {
|
1020 |
+
"content": "__zu__",
|
1021 |
+
"lstrip": false,
|
1022 |
+
"normalized": false,
|
1023 |
+
"rstrip": false,
|
1024 |
+
"single_word": false,
|
1025 |
+
"special": true
|
1026 |
+
}
|
1027 |
+
},
|
1028 |
+
"additional_special_tokens": [
|
1029 |
+
"__af__",
|
1030 |
+
"__am__",
|
1031 |
+
"__ar__",
|
1032 |
+
"__as__",
|
1033 |
+
"__ast__",
|
1034 |
+
"__ay__",
|
1035 |
+
"__az__",
|
1036 |
+
"__ba__",
|
1037 |
+
"__be__",
|
1038 |
+
"__bg__",
|
1039 |
+
"__bn__",
|
1040 |
+
"__br__",
|
1041 |
+
"__bs__",
|
1042 |
+
"__ca__",
|
1043 |
+
"__ceb__",
|
1044 |
+
"__cjk__",
|
1045 |
+
"__cs__",
|
1046 |
+
"__cy__",
|
1047 |
+
"__da__",
|
1048 |
+
"__de__",
|
1049 |
+
"__dyu__",
|
1050 |
+
"__el__",
|
1051 |
+
"__en__",
|
1052 |
+
"__es__",
|
1053 |
+
"__et__",
|
1054 |
+
"__fa__",
|
1055 |
+
"__ff__",
|
1056 |
+
"__fi__",
|
1057 |
+
"__fr__",
|
1058 |
+
"__fy__",
|
1059 |
+
"__ga__",
|
1060 |
+
"__gd__",
|
1061 |
+
"__gl__",
|
1062 |
+
"__gu__",
|
1063 |
+
"__ha__",
|
1064 |
+
"__he__",
|
1065 |
+
"__hi__",
|
1066 |
+
"__hr__",
|
1067 |
+
"__ht__",
|
1068 |
+
"__hu__",
|
1069 |
+
"__hy__",
|
1070 |
+
"__id__",
|
1071 |
+
"__ig__",
|
1072 |
+
"__ilo__",
|
1073 |
+
"__is__",
|
1074 |
+
"__it__",
|
1075 |
+
"__ja__",
|
1076 |
+
"__jv__",
|
1077 |
+
"__ka__",
|
1078 |
+
"__kac__",
|
1079 |
+
"__kam__",
|
1080 |
+
"__kea__",
|
1081 |
+
"__kg__",
|
1082 |
+
"__kk__",
|
1083 |
+
"__km__",
|
1084 |
+
"__kmb__",
|
1085 |
+
"__kmr__",
|
1086 |
+
"__kn__",
|
1087 |
+
"__ko__",
|
1088 |
+
"__ku__",
|
1089 |
+
"__ky__",
|
1090 |
+
"__lb__",
|
1091 |
+
"__lg__",
|
1092 |
+
"__ln__",
|
1093 |
+
"__lo__",
|
1094 |
+
"__lt__",
|
1095 |
+
"__luo__",
|
1096 |
+
"__lv__",
|
1097 |
+
"__mg__",
|
1098 |
+
"__mi__",
|
1099 |
+
"__mk__",
|
1100 |
+
"__ml__",
|
1101 |
+
"__mn__",
|
1102 |
+
"__mr__",
|
1103 |
+
"__ms__",
|
1104 |
+
"__mt__",
|
1105 |
+
"__my__",
|
1106 |
+
"__ne__",
|
1107 |
+
"__nl__",
|
1108 |
+
"__no__",
|
1109 |
+
"__ns__",
|
1110 |
+
"__ny__",
|
1111 |
+
"__oc__",
|
1112 |
+
"__om__",
|
1113 |
+
"__or__",
|
1114 |
+
"__pa__",
|
1115 |
+
"__pl__",
|
1116 |
+
"__ps__",
|
1117 |
+
"__pt__",
|
1118 |
+
"__qu__",
|
1119 |
+
"__ro__",
|
1120 |
+
"__ru__",
|
1121 |
+
"__sd__",
|
1122 |
+
"__shn__",
|
1123 |
+
"__si__",
|
1124 |
+
"__sk__",
|
1125 |
+
"__sl__",
|
1126 |
+
"__sn__",
|
1127 |
+
"__so__",
|
1128 |
+
"__sq__",
|
1129 |
+
"__sr__",
|
1130 |
+
"__ss__",
|
1131 |
+
"__su__",
|
1132 |
+
"__sv__",
|
1133 |
+
"__sw__",
|
1134 |
+
"__ta__",
|
1135 |
+
"__te__",
|
1136 |
+
"__tg__",
|
1137 |
+
"__th__",
|
1138 |
+
"__ti__",
|
1139 |
+
"__tl__",
|
1140 |
+
"__tn__",
|
1141 |
+
"__tr__",
|
1142 |
+
"__uk__",
|
1143 |
+
"__umb__",
|
1144 |
+
"__ur__",
|
1145 |
+
"__uz__",
|
1146 |
+
"__vi__",
|
1147 |
+
"__wo__",
|
1148 |
+
"__xh__",
|
1149 |
+
"__yi__",
|
1150 |
+
"__yo__",
|
1151 |
+
"__zh__",
|
1152 |
+
"__zu__"
|
1153 |
+
],
|
1154 |
+
"bos_token": "<s>",
|
1155 |
+
"clean_up_tokenization_spaces": true,
|
1156 |
+
"eos_token": "</s>",
|
1157 |
+
"language_codes": "m2m100",
|
1158 |
+
"model_max_length": 1024,
|
1159 |
+
"num_madeup_words": 0,
|
1160 |
+
"pad_token": "<pad>",
|
1161 |
+
"sep_token": "</s>",
|
1162 |
+
"sp_model_kwargs": {},
|
1163 |
+
"src_lang": "en",
|
1164 |
+
"tgt_lang": null,
|
1165 |
+
"tokenizer_class": "M2M100Tokenizer",
|
1166 |
+
"unk_token": "<unk>"
|
1167 |
+
}
|
vocab.json
ADDED
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|
|