Create README.md

README.md

@@ -0,0 +1,55 @@
+---
+license: apache-2.0
+datasets:
+- pritish/finance_instruct_data_2k
+language:
+- en
+library_name: adapter-transformers
+pipeline_tag: text-generation
+tags:
+- finance
+---
+
+## Model Details
+
+<!-- Provide a longer summary of what this model is. -->
+
+- **Developed by:** SGX Analytics LLC
+- **Model type:** LLaMA3
+- **Language(s):** English
+- **License:** Apache 2.0
+- **Finetuned from model: meta-llama/Meta-Llama-3-8B** 
+
+## Uses
+
+This model is primarily intended for use by finance professionals, analysts, investors, and other individuals or organizations operating in the finance and investment domain. The model has been trained on a large corpus of financial data, reports, news articles, and other relevant sources, allowing it to possess substantial knowledge and understanding of finance-related topics.
+
+The foreseeable users of this model include, but are not limited to:
+
+- Financial analysts and advisors seeking to leverage the model's knowledge for research, analysis, and investment decision-making processes.
+- Investment firms and asset management companies that may utilize the model for portfolio management, risk assessment, and identifying potential investment opportunities.
+- Corporate finance departments within companies, where the model could assist in financial planning, forecasting, and strategic decision-making.
+- Academic researchers and students in the fields of finance, economics, and related disciplines, who could leverage the model for research purposes or as an educational resource.
+- Journalists and media professionals covering financial news and events, who may use the model to enhance their understanding of complex financial concepts and terminologies.
+
+It is important to note that while the model possesses extensive financial knowledge, it should be used as a supplementary tool to support and inform decision-making processes, rather than as the sole determinant. Human expertise, critical analysis, and due diligence should always be exercised when making financial decisions, as the model's outputs may contain biases or inaccuracies.
+
+## How to use
+
+This model is provided in the GGUF format. To use this model effectively, it is recommended to leverage the LMStudio platform, a user-friendly interface designed specifically for working with GGUF models.
+
+LMStudio provides a seamless environment for loading and interacting with GGUF models like `lmsanch/sgx-finance-enterprise-gguf`. It offers a range of features and tools that allow users to easily query the model, explore its capabilities, and integrate it into their workflows or applications.
+
+## Limitations
+
+It is crucial to understand that this model, like any language model, is not perfect and may exhibit certain limitations and drawbacks. Users should be aware of the following potential issues:
+
+1. **Hallucinations and Factual Errors**: The model may generate outputs that contain hallucinated or factually incorrect information, particularly when dealing with specific details or up-to-date data. While the model has been trained on a vast corpus of financial knowledge, its outputs should be cross-checked and verified against authoritative sources.
+
+2. **Biases and Subjectivity**: As with any machine learning model, `lmsanch/sgx-finance-enterprise-gguf` may exhibit biases inherent in its training data or the modeling process itself. Its outputs may reflect certain biases or subjective perspectives, which could influence the interpretations or recommendations provided.
+
+3. **Lack of Real-Time Updates**: The model's knowledge is based on the training data it was exposed to during the development phase. While this data covers a wide range of financial concepts and information, it may not reflect the latest real-time developments, market shifts, or breaking news events.
+
+4. **Unfiltered Content**: The model does not have built-in filters or safeguards to prevent the generation of potentially harmful, offensive, or inappropriate content. Users should exercise caution and apply their own filtering mechanisms when necessary.
+
+It is strongly recommended to use the `lmsanch/sgx-finance-enterprise-gguf` model as a supplementary tool and to exercise human oversight, critical thinking, and due diligence when making important financial decisions or relying on the model's outputs. Users should always cross-reference and verify the information provided by the model against authoritative and up-to-date sources before taking any consequential actions.