Update README.md

README.md

@@ -1,3 +1,112 @@
----
-license: llama3
----
+---
+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.
+
+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