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README.md
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base_model:
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pipeline_tag: translation
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tags:
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- not-for-all-audiences
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---
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# Model Card for Model ID
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## Uses
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This model is a toy example to showcase how to teach an LLM French slang, it can be used to generate funny translation in argot.
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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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Since the model is trained to translate in slang, some generated content can be considered offensive or inappropriate.
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## How to Get Started with the Model
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Use the code
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[More Information Needed]
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### Training Data
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https://www.kaggle.com/datasets/optimo/french-kaira-training
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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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Training code is fully accesible here: https://www.kaggle.com/code/optimo/kaira-adapting-gemma2-to-local-slang-french/
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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:** bf16
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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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### Framework versions
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base_model:
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- google/gemma-2-2b-it
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pipeline_tag: translation
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---
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# Model Card for Model ID
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## Uses
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This model is a toy example to showcase how to teach an LLM French slang, it can be used to generate funny translation in argot.
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## Bias, Risks, and Limitations
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Since the model is trained to translate in slang, some generated content can be considered offensive or inappropriate.
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## How to Get Started with the Model
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Use the code from Kaggle here : https://www.kaggle.com/code/optimo/kaira-adapting-gemma2-to-local-slang-french/
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Or use the HF Space: Coming
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[More Information Needed]
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### Training Data
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https://www.kaggle.com/datasets/optimo/french-kaira-training
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### Training Procedure
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Training code is fully accesible here: https://www.kaggle.com/code/optimo/kaira-adapting-gemma2-to-local-slang-french/
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#### Training Hyperparameters
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- **Training regime:** bf16
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[More Information Needed]
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### Framework versions
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