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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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- 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 below to get started with the model.
 
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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 <!--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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- ## 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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- #### 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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- [More Information Needed]
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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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- <!-- 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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- **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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  ### 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