Fibonacci 2 14B

🚀 Fibonacci-2-14b Model

The Fibonacci-2-14b is a large language model (LLM) designed to excel in natural language processing (NLP) tasks and textual conversations. With 14 billion parameters, it offers high - performance capabilities for a wide range of language - related applications.

🚀 Quick Start

To start using the Fibonacci-2-14b model, you can leverage popular libraries like Hugging Face's transformers. Here's a basic code example to get you going:

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("fibonacciai/fibonacci-2-14b")
model = AutoModelForCausalLM.from_pretrained("fibonacciai/fibonacci-2-14b")

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: Phi 4
• Number of Parameters: 14 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: Create creative and diverse texts.
• Question Answering: Provide accurate responses to user inquiries.
• Machine Translation: Translate texts between different languages.
• Sentiment Analysis: Identify sentiments present in texts.

📚 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.

🔗 Links

• Model Logo
• YouTube Video
• Official Website