HuangXinBa/tiny-gpt2-1b-textgen

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Model Details

Model Description

This is a GPT-2 1B model fine-tuned on a subset of the Wikipedia corpus for text generation tasks. The model is capable of generating coherent and creative continuations given a prompt. It was trained to predict the next token given previous context using a causal language modeling objective.

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• Language(s) (NLP): en
• License: apache-2.0
• Finetuned from model [optional]: gpt2

Model Sources [optional]

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Uses

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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

A 1% subset of the English Wikipedia corpus was used. Data was preprocessed by removing formatting artifacts, tokenized using a custom GPT-2 tokenizer trained from scratch.

Training Procedure

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Training Hyperparameters

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Evaluation

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Results

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Summary

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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 [optional]

Model Architecture and Objective

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