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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

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:

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 GitHub repository.

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GGUF
Model size
1.1B params
Architecture
llama

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Inference Examples
Unable to determine this model's library. Check the docs .

Dataset used to train erfanzar/LinguaMatic-Coder-INST-1B-GGUF

Collection including erfanzar/LinguaMatic-Coder-INST-1B-GGUF