Improve model card
Browse filesThis PR improves the model card by:
* Adding `pipeline_tag: text-generation`
* Adding `library_name: transformers`
* Adding the link to the Github repo
README.md
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library_name: transformers
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tags: []
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# Model Card for Model
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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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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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### Model Sources
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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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[More Information Needed]
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### Downstream Use [optional]
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[More Information Needed]
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### Out-of-Scope Use
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[More Information Needed]
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## Bias, Risks, and Limitations
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[More Information Needed]
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### Recommendations
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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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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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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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#### 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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## Technical Specifications [optional]
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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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library_name: transformers
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pipeline_tag: text-generation
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license: mit
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tags: []
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# Model Card for Perspectival Language Model
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This model is associated with the paper "Pretraining Language Models for Diachronic Linguistic Change Discovery" and is designed for text generation, particularly in the context of historical linguistics.
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## Model Details
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### Model Description
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This 🤗 transformers model was trained to study diachronic linguistic change by pretraining language models on historical text corpora.
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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:** Llama (Please verify and specify the exact architecture)
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- **Language(s) (NLP):** English (Please specify all languages if applicable)
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- **License:** MIT (Please verify and correct if needed)
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- **Finetuned from model [optional]:** [Please specify base model if applicable]
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### Model Sources
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- **Repository:** <https://github.com/comp-int-hum/historical-perspectival-lm>
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- **Paper [optional]:** [https://huggingface.co/papers/2504.05523](https://huggingface.co/papers/2504.05523)
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- **Demo [optional]:** [More Information Needed]
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## Uses
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### Direct Use
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The model can be used directly for generating text, especially when exploring historical language patterns.
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### Downstream Use [optional]
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This model can be fine-tuned for tasks like language change detection or stylistic analysis across time periods.
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### Out-of-Scope Use
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The model may not perform well on tasks requiring contemporary language understanding.
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## Bias, Risks, and Limitations
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The model's training data reflects biases in historical texts, which could appear in the model's outputs.
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### Recommendations
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Users should be aware of potential biases and the model's limitations with modern language.
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## How 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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[More Information Needed]
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### Training Procedure
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[More Information Needed]
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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]
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#### Speeds, Sizes, Times [optional]
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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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[More Information Needed]
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#### Metrics
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[More Information Needed]
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### Results
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#### Summary
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[More Information Needed]
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## Model Examination [optional]
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[More Information Needed]
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## Environmental Impact
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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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## Citation [optional]
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[More Information Needed]
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## Glossary [optional]
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[More Information Needed]
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## More Information [optional]
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