---
datasets:
- laion/gpt4v-dataset
library_name: transformers
---
Model Card: AdemGPT
1. General Information
Model Name: AdemGPT
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.

2. Authors and Affiliations
Authors: [Trat80]
Affiliations: [N/A]

3. Model Functionality
Supported Tasks: Text generation, Answering questions, Text to text, etc.
Supported Languages: Mainly Spanish.
Examples of Use: Generation of summaries, creative writing, informal conversation, among others.

4. Dataset and Training
Dataset Origin: Created from multiple sources of text in Spanish (books, online articles, conversations, etc.).
Dataset Size: Contains millions of examples of text in Spanish.
Training Procedures: The GPT-3 architecture was used and trained for several weeks in a high-performance environment.

5. Model Performance
Evaluation Metrics: Text coherence, precision in questions and answers, language fluency, etc.
Results: Achieved high scores on text generation tests and language processing tasks.

6. Ethical Considerations
Bias Considerations: Efforts have been made to mitigate bias, but there may be some inherent biases in the training data.
Privacy and Security: The model does not store user information and caution should be taken when using it with sensitive data.

7. Limitations of the Model
Known Limitations: Cannot provide information in other languages ​​and may have difficulty with very specialized or technical concepts.

8. License and Conditions of Use
License: [cc-by-nc-sa4.0]
Conditions of Use: The model is available for non-commercial and educational use. It is recommended to review the license terms.

## Example

Install request:

pip install requests

After that, put that in you python:

import requests
import json


model_name = 'Trat80/AdemGPT'  
api_token = 'tu_api_token'  # You token api


input_text = "Hi! My Name Is AdemGPT!"


headers = {
    'Authorization': f'Bearer {api_token}',
    'Content-Type': 'application/json'
}

data = {
    'inputs': input_text,
    'parameters': {
        'max_new_tokens': 100
    }
}

response = requests.post(f'https://api-inference.huggingface.co/models/{model_name}', headers=headers, data=json.dumps(data))

if response.status_code == 200:
    generated_text = response.json().get('generated_text')
    print(generated_text)
else:
    print("Error en la solicitud:", response.status_code, response.text)