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--- |
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datasets: |
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- laion/gpt4v-dataset |
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library_name: transformers |
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--- |
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Model Card: AdemGPT |
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1. General Information |
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Model Name: AdemGPT |
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Description: AdemGPT is a pre-trained generative language model that seeks to generate coherent and relevant text based on a wide spectrum of linguistic tasks. |
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2. Authors and Affiliations |
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Authors: [Trat80] |
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Affiliations: [N/A] |
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3. Model Functionality |
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Supported Tasks: Text generation, Answering questions, Text to text, etc. |
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Supported Languages: Mainly Spanish. |
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Examples of Use: Generation of summaries, creative writing, informal conversation, among others. |
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4. Dataset and Training |
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Dataset Origin: Created from multiple sources of text in Spanish (books, online articles, conversations, etc.). |
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Dataset Size: Contains millions of examples of text in Spanish. |
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Training Procedures: The GPT-3 architecture was used and trained for several weeks in a high-performance environment. |
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5. Model Performance |
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Evaluation Metrics: Text coherence, precision in questions and answers, language fluency, etc. |
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Results: Achieved high scores on text generation tests and language processing tasks. |
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6. Ethical Considerations |
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Bias Considerations: Efforts have been made to mitigate bias, but there may be some inherent biases in the training data. |
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Privacy and Security: The model does not store user information and caution should be taken when using it with sensitive data. |
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7. Limitations of the Model |
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Known Limitations: Cannot provide information in other languages and may have difficulty with very specialized or technical concepts. |
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8. License and Conditions of Use |
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License: [cc-by-nc-sa4.0] |
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Conditions of Use: The model is available for non-commercial and educational use. It is recommended to review the license terms. |
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## Ejemplo de Uso |
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Puedes interactuar con el modelo AdemGPT utilizando la biblioteca Transformers de Hugging Face. Aquí tienes un ejemplo simple de cómo generar texto: |
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```python |
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from transformers import pipeline |
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generator = pipeline('text-generation', model='Trat80/AdemGPT') |
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generated_text = generator("Una vez en un lugar lejano, ", max_length=100, num_return_sequences=1) |
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print(generated_text) |
