metadata

license: apache-2.0
language:
  - en
co2_eq_emissions:
  emissions: 0.05
  source: https://mlco2.github.io/impact
  training_type: fine-tuning
  geographical_location: >-
    Brooklyn, NY, USA. To check your compute's electricity grid, you can check
    out https://app.electricitymap.org.
  hardware_used: T4 (Google Colab)

Model Card for Model ID

This modelcard aims to be a base template for new models. It has been generated using this raw template.

Model Details

Finetuned using aitextgen, an easy-to-use library by Max Woolf for creative text generation. more here: https://github.com/minimaxir/aitextgen

Model Description

finetuned using aitextgen on a dataset including philosophy books, r/showerthoughts, and original texts generated by chatGPT. Please report any offensive content, etc!

Developed by: Colleen Macklin
Model type: GPT Neo Small (125m)
Language(s) (NLP): en
License: [More Information Needed]
Finetuned from model [optional]: GPT Neo Small (125m)

Uses

For creative projects and dialogue generation.

Bias, Risks, and Limitations

This model generates unsupervised random output has the potential to offend with biased outputs. Please use responsibly.

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

license: apache-2.0 language: - en co2_eq_emissions: emissions: .05kg Co2 eq. source: "https://mlco2.github.io/impact" training_type: "fine-tuning" geographical_location: "Brooklyn, NY, USA. To check your compute's electricity grid, you can check out https://app.electricitymap.org." hardware_used: "T4 (Google Colab)"

Hardware Type: [T4]
Hours used: [.5]
Cloud Provider: [Google Colab]
Compute Region: [Brooklyn, NY, USA]
Carbon Emitted: [.05kg Co2 eq.]