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---
datasets:
- erfanzar/UltraChat-Mixin
language:
- en
- fr
- es
metrics:
- accuracy
pipeline_tag: text-generation
tags:
- code
---
# LinguaMatic
LinguaMatic is an advanced AI model designed to handle a wide range of Natural Language Processing (NLP) tasks. With its powerful capabilities, LinguaMatic can assist with tasks such as text classification, sentiment analysis, language translation, question answering, and much more.
## EasyDel
The model is finetuned Using a custom version of UltraChat on TPU-v4 POD using [EasyDel](https://github.com/erfanzar/EasyDeL)
## Prompting Method
LinguaMatic utilizes the OC prompting method to generate responses. This method, named after the friendly and intelligent llama, enhances the model's ability to engage in meaningful conversations. The `prompt_model` function provided below demonstrates how the llama2 prompting method is implemented:
```python
def prompt_model(
problem:str,
system = "You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions."
):
prompt = f"<|system|>\n{system}</s>\n<|user|>\n{problem}</s>\n<|assistant|>\n"
return prompt
```
The `prompt_model` function takes a `problem` as input, along with the `system`. It generates a formatted text that includes the system prompt, user inputs, and the current message. This approach allows LinguaMatic to maintain context and provide more coherent and context-aware responses.
Remember this model is instruction-tuned with Coding Problems only and will take a static system input
use system as
`You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.`
## Contributing
We welcome contributions to enhance LinguaMatic's capabilities and improve its performance. If you encounter any issues or have suggestions for improvement, please feel free to submit a pull request or open an issue on [EasyDel](https://github.com/erfanzar/EasyDeL) GitHub repository.
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