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opt-350m-open-data-understanding

Text Generation
Transformers
PyTorch
opt
Generated from Trainer
qa
open data
opt-350
opt-350m
Inference Endpoints
text-generation-inference
Model card Files Community
opt-350m-open-data-understanding / README.md
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metadata
license: other
base_model: facebook/opt-350m
tags:
  - generated_from_trainer
  - qa
  - open data
  - opt
  - opt-350
  - opt-350m
metrics:
  - accuracy
widget:
  - text: |-
      # [PAPER]
       Pope John Paul II (Latin: Ioannes Paulus II; Italian: Giovanni Paolo II; Polish: Jan Paweł II; born Karol Józef Wojtyła [ˈkarɔl ˈjuzɛv vɔjˈtɨwa];[b] 18 May 1920 – 2 April 2005) was head of the Catholic Church and sovereign of the Vatican City State from 1978 until his death in 2005. He was later canonised as Pope Saint John Paul II. In his youth, Wojtyła dabbled in stage acting. He graduated with excellent grades from an all-boys high school in Wadowice, Poland, shortly before the start of World War II in 1938. During the war, to avoid being kidnapped and sent off to a German slave labor camp, he signed up for work in harsh conditions in a quarry. Wojtyła eventually took up acting and developed a love for the profession and participated at a local theater. The linguistically skilled Wojtyła wanted to study Polish at university. Encouraged by a conversation with Adam Stefan Sapieha, he decided to study theology and become a priest. Eventually, Wojtyła rose to the position of Archbishop of Kraków and then a cardinal, both positions held by his mentor. Wojtyła was elected pope on the third day of the second papal conclave of 1978 (becoming one of the youngest popes in history), which was called after John Paul I, who had been elected in the first papal conclave of 1978 earlier in August to succeed Pope Paul VI, died after 33 days. Wojtyła adopted the name of his predecessor in tribute to him.[20] John Paul II was the first non-Italian pope since Adrian VI in the 16th century, as well as the third-longest-serving pope in history after Pius IX and St. Peter. John Paul II attempted to improve the Catholic Church's relations with Judaism, Islam, and the Eastern Orthodox Church in the spirit of ecumenism, holding atheism as the greatest threat. He maintained the Church's previous positions on such matters as abortion, artificial contraception, the ordination of women, and a celibate clergy, and although he supported the reforms of the Second Vatican Council, he was seen as generally conservative in their interpretation.[21][22] He put emphasis on family and identity, while questioning consumerism, hedonism and the pursuit of wealth. He was one of the most travelled world leaders in history, visiting 129 countries during his pontificate. As part of his special emphasis on the universal call to holiness, he beatified 1,344,[23] and also canonised 483 people, more than the combined tally of his predecessors during the preceding five centuries. By the time of his death, he had named most of the College of Cardinals, consecrated or co-consecrated many of the world's bishops, and ordained many priests.[24] He has been credited with fighting against dictatorships for democracy and with helping to end Communist rule in his native Poland and the rest of Europe.[25] Under John Paul II, the Catholic Church greatly expanded its influence in Africa and Latin America, and retained its influence in Europe and the rest of the world.

      ## [UNDERSTANDING]
       This section presents a brief account 
datasets:
  - ccore/open_data_understanding
pipeline_tag: text-generation

OPT_350_open_data_understanding

Description

This model has been trained to understand and respond to any content inserted after the [PAPER] tag. It uses advanced language modeling techniques to understand the context, structure, and underlying goals of the input text.

How to use

To interact with this template, place your text after the [PAPER] tag. The model will process the text and respond accordingly. For example:

[PAPER] Your text here...

Example

[PAPER] We present a scalable method to build a high-quality instruction-following language model...

The model will understand and respond to your text according to its context and content.

Comprehension Sections

[UNDERSTANDING]

This section provides a detailed analysis and decomposition of the inserted text, facilitating the understanding of the content.

[QUESTIONS AND ANSWERS]

This section addresses questions and answers that could arise based on the text provided.

[OBJECTION AND REPLY]

This section addresses any objections and responses that could arise from analysis of the text.

Common questions

  • What can this model do?

    • This model can understand and respond to any text placed after the [PAPER] tag.

  • Is a specific format necessary?

    • No, the model is quite flexible regarding the text format.

  • How does this model perform?

    • The model outperforms other LLaMa-based models on the Alpaca leaderboard, demonstrating a highly effective alignment.

Warnings

  • This model was trained on a diverse corpus, but may still have bias or limitations.
  • Continuous validation of the model and its output is essential.

Contact and Support

For more information, visit Hugging Face.