---
license: llama3
datasets:
- taddeusb90/finbro-v0.1.0
language:
- en
library_name: transformers
tags:
- finance
---

Fibro v0.1.0 Llama 3 8B Model with 1Million token context window
======================

Model Description
-----------------

The Fibro Llama 3 8B model is language model optimized for financial applications. This model aims to enhance financial analysis, automate data extraction, and improve financial literacy across various user expertise levels. It utilizes a massive 1 million token context window. 
This is just a sneak peek into what's coming, and future releases will be done periodically consistently improving it's performance.

![FinBro](https://huggingface.co/taddeusb90/finbro-v0.1.0-llama-3-8B-instruct-1m-POSE/blob/main/437210082_369067905507560_2052449041654631065_n.png)

Training:
-----------------

The model is still training, I will be sharing new incremental releases while it's improving so you have time to play around with it.
![Loss](https://huggingface.co/taddeusb90/finbro-v0.1.0-llama-3-8B-instruct-1m-POSE/resolve/main/W%26B%20Chart%2006_05_2024%2C%2015_57_42.png)
![Evaluation Loss](https://huggingface.co/taddeusb90/finbro-v0.1.0-llama-3-8B-instruct-1m-POSE/resolve/main/W%26B%20Chart%2006_05_2024%2C%2015_58_01.png)

What's Next?
-----------

*   **Extended Capability:** Continue training on the 8B model as it hasn't converged yet as I only scratched the surface here and transitioning to scale up with a 70B model for deeper insights and broader financial applications.
*   **Dataset Expansion:** Continuous enhancement by integrating more diverse and comprehensive real and synthetic financial data.
*   **Advanced Financial Analysis:** Future versions will support complex financial decision-making processes by interpreting and analyzing financial data within agentive workflows.
*   **Incremental Improvements:** Regular updates are made to increase the model's efficiency and accuracy and extend it's capabilities in financial tasks.

Model Applications
------------------

*   **Information Extraction:** Automates the process of extracting valuable data from unstructured financial documents.
*   **Financial Literacy:** Provides explanations of financial documents at various levels, making financial knowledge more accessible.


How to Use
----------

Here is how to load and use the model in your Python projects:


```python
from transformers import AutoModelForCausalLM, AutoTokenizer  

model_name = "taddeusb90/finbro-v0.1.0-llama-3-8B-instruct-1m-POSE" 
tokenizer = AutoTokenizer.from_pretrained(model_name) 

model = AutoModelForCausalLM.from_pretrained(model_name)  
text = "Your financial query here" 

inputs = tokenizer(text, return_tensors="pt") 

outputs = model.generate(inputs['input_ids']) 

print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

Training Data
-------------

The Fibro Llama 3 8B model was trained on the Finbro Dataset, an extensive compilation of over 300,000 entries sourced from Investopedia and Sujet Finance. This dataset includes structured Q&A pairs, financial reports, and a variety of financial tasks pooled from multiple datasets. 

The dataset can be found [here](https://huggingface.co/datasets/taddeusb90/finbro-v0.1.0)

This dataset will be extended to contain real and synthetic data on a wide range of financial tasks such as:
- Investment valuation
- Value investing
- Security analysis
- Derivatives
- Asset and portfolio management
- Financial information extraction
- Quantitative finance
- Econometrics
- Applied computer science in finance
and much more

Notice
--------

Please exercise caution and use it at your own risk. I assume no responsibility for any losses incurred if used.


Licensing
---------

This model is released under the [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/blob/main/LICENSE).


Citation
--------

If you use this model in your research, please cite it as follows:


```bibtex
@misc{
    finbro_v0.1.0-llama-3-8B-1m-POSE,   
    author = {Taddeus Buica},   title = {Fibro Llama 3 8B Model for Financial Analysis},   
    year = {2024},   
    journal = {Hugging Face repository},
    howpublished = {\url{https://huggingface.co/taddeusb90/finbro-v0.1.0-llama-3-8B-instruct-1m-POSE}} 
}
```

Special thanks to the folks from AI@Meta for powering this project with their awesome models.

References
--------

[[1](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)] Llama 3 Model Card by AI@Meta, Year: 2024

[[2](https://huggingface.co/datasets/sujet-ai/Sujet-Finance-Instruct-177k)] Sujet Finance Dataset

[[3](https://huggingface.co/datasets/FinLang/investopedia-instruction-tuning-dataset)] Dataset Card for investopedia-instruction-tuning