sylvain471
commited on
Commit
•
ad6a0f9
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Parent(s):
91e8851
Upload processor
Browse files- README.md +199 -0
- added_tokens.json +10 -0
- preprocessor_config.json +44 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +55 -0
- tokenizer.json +0 -0
- tokenizer_config.json +124 -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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"</s_carburant>": 57526,
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"</s_volume>": 57528,
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"<s_carburant>": 57525,
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"<s_fuel-v3>": 57529,
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"<s_iitcdip>": 57523,
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"<s_synthdog>": 57524,
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"<s_volume>": 57527,
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"<sep/>": 57522
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}
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preprocessor_config.json
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{
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"_valid_processor_keys": [
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"images",
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"do_resize",
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"size",
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"resample",
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"do_thumbnail",
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"do_align_long_axis",
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"do_pad",
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"random_padding",
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"do_rescale",
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"rescale_factor",
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"do_normalize",
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"image_mean",
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"image_std",
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"return_tensors",
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"data_format",
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"input_data_format"
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],
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"do_align_long_axis": false,
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"do_normalize": true,
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"do_pad": true,
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"do_rescale": true,
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"do_resize": true,
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"do_thumbnail": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "DonutImageProcessor",
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"processor_class": "DonutProcessor",
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": [
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960,
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1280
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]
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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:cb9e3dce4c326195d08fc3dd0f7e2eee1da8595c847bf4c1a9c78b7a82d47e2d
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size 1296245
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<s_iitcdip>",
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"<s_synthdog>"
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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": true,
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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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1 |
+
{
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2 |
+
"added_tokens_decoder": {
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"0": {
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4 |
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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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26 |
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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": 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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35 |
+
"57521": {
|
36 |
+
"content": "<mask>",
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37 |
+
"lstrip": true,
|
38 |
+
"normalized": true,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": true
|
42 |
+
},
|
43 |
+
"57522": {
|
44 |
+
"content": "<sep/>",
|
45 |
+
"lstrip": false,
|
46 |
+
"normalized": true,
|
47 |
+
"rstrip": false,
|
48 |
+
"single_word": false,
|
49 |
+
"special": false
|
50 |
+
},
|
51 |
+
"57523": {
|
52 |
+
"content": "<s_iitcdip>",
|
53 |
+
"lstrip": false,
|
54 |
+
"normalized": false,
|
55 |
+
"rstrip": false,
|
56 |
+
"single_word": false,
|
57 |
+
"special": true
|
58 |
+
},
|
59 |
+
"57524": {
|
60 |
+
"content": "<s_synthdog>",
|
61 |
+
"lstrip": false,
|
62 |
+
"normalized": false,
|
63 |
+
"rstrip": false,
|
64 |
+
"single_word": false,
|
65 |
+
"special": true
|
66 |
+
},
|
67 |
+
"57525": {
|
68 |
+
"content": "<s_carburant>",
|
69 |
+
"lstrip": false,
|
70 |
+
"normalized": true,
|
71 |
+
"rstrip": false,
|
72 |
+
"single_word": false,
|
73 |
+
"special": false
|
74 |
+
},
|
75 |
+
"57526": {
|
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"content": "</s_carburant>",
|
77 |
+
"lstrip": false,
|
78 |
+
"normalized": true,
|
79 |
+
"rstrip": false,
|
80 |
+
"single_word": false,
|
81 |
+
"special": false
|
82 |
+
},
|
83 |
+
"57527": {
|
84 |
+
"content": "<s_volume>",
|
85 |
+
"lstrip": false,
|
86 |
+
"normalized": true,
|
87 |
+
"rstrip": false,
|
88 |
+
"single_word": false,
|
89 |
+
"special": false
|
90 |
+
},
|
91 |
+
"57528": {
|
92 |
+
"content": "</s_volume>",
|
93 |
+
"lstrip": false,
|
94 |
+
"normalized": true,
|
95 |
+
"rstrip": false,
|
96 |
+
"single_word": false,
|
97 |
+
"special": false
|
98 |
+
},
|
99 |
+
"57529": {
|
100 |
+
"content": "<s_fuel-v3>",
|
101 |
+
"lstrip": false,
|
102 |
+
"normalized": true,
|
103 |
+
"rstrip": false,
|
104 |
+
"single_word": false,
|
105 |
+
"special": false
|
106 |
+
}
|
107 |
+
},
|
108 |
+
"additional_special_tokens": [
|
109 |
+
"<s_iitcdip>",
|
110 |
+
"<s_synthdog>"
|
111 |
+
],
|
112 |
+
"bos_token": "<s>",
|
113 |
+
"clean_up_tokenization_spaces": true,
|
114 |
+
"cls_token": "<s>",
|
115 |
+
"eos_token": "</s>",
|
116 |
+
"mask_token": "<mask>",
|
117 |
+
"model_max_length": 1000000000000000019884624838656,
|
118 |
+
"pad_token": "<pad>",
|
119 |
+
"processor_class": "DonutProcessor",
|
120 |
+
"sep_token": "</s>",
|
121 |
+
"sp_model_kwargs": {},
|
122 |
+
"tokenizer_class": "XLMRobertaTokenizer",
|
123 |
+
"unk_token": "<unk>"
|
124 |
+
}
|