library_name: transformers
tags: []
pipeline_tag: text-generation
license: mit
Model Card for Model ID
Model based on the paper Pretraining Language Models for Diachronic Linguistic Change Discovery.
Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. It is a causal language model trained for historical language understanding.
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- Model type: Causal language model
- Language(s) (NLP): English
- License: MIT
- Finetuned from model [optional]: Llama 2
Model Sources
- Repository: https://github.com/comp-int-hum/historical-perspectival-lm
- Paper: https://huggingface.co/papers/2504.05523
Uses
Direct Use
This model can be used for generating text in a style representative of the historical period it was trained on.
Downstream Use
This model can be finetuned for specific tasks, such as diachronic linguistics.
Out-of-Scope Use
This model is not intended for use cases where a modern understanding of language is required.
Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
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Training Procedure
Preprocessing
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Training Hyperparameters
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Speeds, Sizes, Times
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Summary
Model Examination
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Technical Specifications
Model Architecture and Objective
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Compute Infrastructure
Hardware
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Software
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Citation
BibTeX:
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APA:
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Glossary
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Model Card Authors
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Model Card Contact
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