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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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- ### Results
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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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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- **BibTeX:**
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- **APA:**
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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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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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+ license: mit
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+ base_model: microsoft/speecht5_tts
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: speecht5_tts-wolof
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+ results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # speecht5_tts-wolof
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+ This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3697
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+
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+ ## Model description
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+ More information needed
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+ ## Intended uses & limitations
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+ More information needed
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+ ## Training and evaluation data
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+ More information needed
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+ ## Training procedure
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 64
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 255000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:-----:|:---------------:|
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+ | 0.5033 | 0.9989 | 562 | 0.4592 |
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+ | 0.471 | 1.9996 | 1125 | 0.4319 |
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+ | 0.4603 | 2.9984 | 1687 | 0.4224 |
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+ | 0.4496 | 3.9991 | 2250 | 0.4135 |
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+ | 0.4418 | 4.9998 | 2813 | 0.4090 |
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+ | 0.4296 | 5.9987 | 3375 | 0.4001 |
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+ | 0.425 | 6.9993 | 3938 | 0.3950 |
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+ | 0.4197 | 8.0 | 4501 | 0.3927 |
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+ | 0.4173 | 8.9989 | 5063 | 0.3888 |
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+ | 0.4133 | 9.9996 | 5626 | 0.3852 |
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+ | 0.4112 | 10.9984 | 6188 | 0.3832 |
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+ | 0.4072 | 11.9991 | 6751 | 0.3808 |
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+ | 0.404 | 12.9998 | 7314 | 0.3788 |
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+ | 0.4055 | 13.9987 | 7876 | 0.3792 |
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+ | 0.401 | 14.9993 | 8439 | 0.3759 |
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+ | 0.3988 | 16.0 | 9002 | 0.3755 |
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+ | 0.3984 | 16.9989 | 9564 | 0.3761 |
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+ | 0.3992 | 17.9996 | 10127 | 0.3735 |
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+ | 0.392 | 18.9984 | 10689 | 0.3731 |
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+ | 0.393 | 19.9991 | 11252 | 0.3730 |
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+ | 0.3945 | 20.9998 | 11815 | 0.3713 |
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+ | 0.3929 | 21.9987 | 12377 | 0.3720 |
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+ | 0.3919 | 22.9993 | 12940 | 0.3736 |
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+ | 0.3907 | 24.0 | 13503 | 0.3702 |
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+ | 0.3893 | 24.9989 | 14065 | 0.3700 |
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+ | 0.3894 | 25.9996 | 14628 | 0.3707 |
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+ | 0.39 | 26.9984 | 15190 | 0.3687 |
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+ | 0.3858 | 27.9991 | 15753 | 0.3712 |
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+ | 0.3874 | 28.9998 | 16316 | 0.3669 |
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+ | 0.3887 | 29.9987 | 16878 | 0.3685 |
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+ | 0.3854 | 30.9993 | 17441 | 0.3670 |
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+ | 0.3856 | 32.0 | 18004 | 0.3697 |
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+ ### Framework versions
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+ - Transformers 4.41.2
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
generation_config.json ADDED
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+ "_from_model_config": true,
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+ "bos_token_id": 0,
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+ "eos_token_id": 2,
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+ "max_length": 1876,
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+ "pad_token_id": 1,
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+ "transformers_version": "4.41.2"
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+ }
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