Trat80/AdemGPT

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)