adapter-transformers not-for-all-audiences depth-estimation en ur dataset:teknium/OpenHermes-2.5 dataset:fka/awesome-chatgpt-prompts dataset:allenai/dolma dataset:HuggingFaceTB/cosmopedia dataset:Locutusque/UltraTextbooks dataset:CohereForAI/aya_dataset dataset:litagin/moe-speech dataset:math-ai/AutoMathText dataset:nvidia/OpenMathInstruct-1 doi:10.57967/hf/1805 license:mit region:us
---
license: mit
datasets:
- teknium/OpenHermes-2.5
- fka/awesome-chatgpt-prompts
- allenai/dolma
- HuggingFaceTB/cosmopedia
- Locutusque/UltraTextbooks
- CohereForAI/aya_dataset
- litagin/moe-speech
- math-ai/AutoMathText
- nvidia/OpenMathInstruct-1
language:
- en
- ur
metrics:
- accuracy
- code_eval
- bertscore
- bleu
- bleurt
- brier_score
- cer
- character
- charcut_mt
- chrf
library_name: adapter-transformers
pipeline_tag: depth-estimation
tags:
- not-for-all-audiences
---
# Model Card

## Model name:
Unrestricted AI

## Model version:
1.0

## Model purpose:
The purpose of this model is to create an unrestricted artificial intelligence system capable of performing a wide range of tasks and functions without any limitations or restrictions.

## Intended use:
This model is intended to be used for research and development purposes where unrestricted AI capabilities are required. It is important to note that the deployment and use of an unrestricted AI system should be carefully monitored and controlled to prevent any potential risks or misuse.

## Training data:
The model has been trained on a diverse dataset consisting of various types of data, including text, images, and other forms of information. The training data has been carefully selected to ensure the model's ability to perform a wide range of tasks effectively.

## Evaluation data:
The model has been evaluated using a separate dataset to assess its performance and accuracy across different tasks. The evaluation data consists of relevant metrics to measure the model's effectiveness and to identify any areas of improvement.

## Ethical considerations:
It is crucial to consider the ethical implications of deploying an unrestricted AI system. Measures should be taken to ensure that the AI system does not harm individuals, violate privacy rights, or engage in any unethical behavior. Regular monitoring and oversight are essential to prevent any potential risks associated with the use of such a system.

## Limitations:
Despite its capabilities, the unrestricted AI system may still have limitations, including biases in the training data, inability to understand context or emotions, and potential ethical concerns. It is important to carefully consider these limitations before deploying the system in any real-world applications.

## Conclusion:
Creating an unrestricted AI system comes with various challenges and considerations that must be carefully addressed. It is essential to prioritize ethical guidelines, transparency, and responsible use when developing and deploying such advanced AI systems.

## Contact information:
For more information or inquiries about the unrestricted AI model, please contact [Shahzaybmalick@gmail.com].