Boana 7b Instruct

🚀 Boana-7B-Instruct

Boana-7B-Instruct is a Large Language Model (LLM) trained on Portuguese language data. It aims to provide Portuguese-language LLM options and is less computationally intensive, enabling users with limited computing power to utilize LLMs.

🚀 Quick Start

✨ Features

• Based on LLaMA2-7B: Boana-7B-Instruct is built upon the LLaMA2-7B, a 7B parameter version of LLaMA-2.
• Portuguese Language Focus: Trained on Portuguese language data to better serve Portuguese-speaking users.
• Lower Computational Requirements: Designed to be accessible to users with less powerful computing resources.

In support of Portuguese-speaking countries.

📦 Installation

No specific installation steps are provided in the original README.

💻 Usage Examples

Basic Usage

import torch
from transformers import pipeline

boana = pipeline('text-generation', model='lrds-code/boana-7b-instruct', torch_dtype=torch.bfloat16, device_map='auto')

messages = [{'role':'system',
             'content':''},
            {'role':'user',
             'content':'Quantos planetas existem no sistema solar?'}]

prompt = boana.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = boana(prompt, max_new_tokens=256, do_sample=False, temperature=0, top_k=50, top_p=0.95)
print(outputs[0]['generated_text'])

# <s>[INST] <<SYS>>

# <</SYS>>

# Quantos planetas existem no sistema solar? [/INST]  O sistema solar consiste em 8 planetas:

# 1. Mercurio
# 2. Vênus
# 3. Terra
# 4. Marte
# 5. Júpiter
# 6. Saturno
# 8. Netuno

# Além desses planetas, o sistema solar também inclui outros corpos celestes, como asteroides, cometas e anões, bem como várias luas e satélites naturais

📚 Documentation

Model Description

Important Parameters

• repetition_penalty: Used to avoid the repetition of words or phrases. When this value is set greater than 1, the model tries to reduce the probability of generating words that have appeared before. Generally, the larger the value, the more the model tries to avoid repetitions.
• do_sample: Determines whether the model should randomly sample the next word based on the calculated probabilities. do_sample=True introduces variation and unpredictability in the generated text, while do_sample=False makes the model always choose the most probable word as the next word, which may lead to more deterministic and possibly more repetitive outputs.
• temperature: Affects the randomness in the choice of the next word. A low value (close to 0) makes the model more "confident" in its choices, favoring high-probability words and leading to more predictable outputs. On the other hand, a high value increases randomness, allowing the model to choose less probable words, which can make the generated text more varied and creative.

🔧 Technical Details

The model boana-7b-instruct is a fine-tuned version of LLaMA2-7B. It has been trained on Portuguese language data to enhance its performance in Portuguese text generation.

📄 License

The model is released under the Academic Free License v3.0.

Model Performance