Fibonacci 2 9b

🚀 Fibonacci-2-9b Model

The Fibonacci-2-9b is a large language model (LLM) based on the Gemma2 architecture, designed to handle natural language processing (NLP) tasks and text conversations effectively. It comes with 9.24 billion parameters, making it a powerful tool in the field of NLP.

• YouTube Video
• Official Website

🚀 Quick Start

To use this model, you can utilize various libraries such as Hugging Face's transformers. Below is a sample code to load and use the model:

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("fibonacciai/fibonacci-2-9b")
model = AutoModelForCausalLM.from_pretrained("fibonacciai/fibonacci-2-9b")

input_text = "Hello! How can I assist you today?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(response)

✨ Features

• Architecture: Gemma2
• Number of Parameters: 9.24 billion
• Formats: GGUF supporting 4-bit (Q4_K_M), 5-bit (Q5_K_M), 8-bit (Q8_0), and 16-bit (F16)
• License: MIT

📦 Applications

• Text Generation: Creating creative and diverse texts
• Question Answering: Providing accurate responses to user inquiries
• Machine Translation: Translating texts between different languages
• Sentiment Analysis: Identifying sentiments present in texts

📚 Documentation

Resources

• Model Page on Hugging Face
• Hugging Face Documentation

Contribution

We welcome your contributions! If you have suggestions for improving the model or have identified any bugs, please share them with us through the Issues section.

📄 License

This model is released under the MIT License. For more information, see the LICENSE file.