Create README.md

README.md

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+---
+# Model Card Metadata
+license: apache-2.0
+library_name: statsmodels
+tags:
+  - time-series
+  - forecasting
+  - ARIMA
+  - financial-data
+datasets:
+  - bitcoin-historical-data
+model_name: ARIMA Bitcoin Forecasting Model
+---
+
+# Model Card for ARIMA Bitcoin Forecasting Model
+
+This ARIMA model is designed to predict Bitcoin market trends using historical data. It is trained on the closing prices of Bitcoin, extracted from the Bitcoin Historical Dataset. The model aims to provide accurate short-term forecasts for cryptocurrency price movements.
+
+## Model Details
+
+### Model Description
+
+- **Developed by:** [Your Name or Organization]
+- **Funded by:** [Optional: Funding Source]
+- **Shared by:** [Your Name or Organization]
+- **Model type:** ARIMA (AutoRegressive Integrated Moving Average)
+- **Language(s):** Not applicable
+- **License:** Apache 2.0
+- **Finetuned from model:** Not applicable
+
+### Model Sources
+
+- **Repository:** [Add your Hugging Face repo URL]
+- **Dataset:** [Bitcoin Historical Data on Kaggle](https://www.kaggle.com/datasets/mczielinski/bitcoin-historical-data)
+- **Demo:** [Optional: Add demo link if available]
+
+## Uses
+
+### Direct Use
+
+This model can be used directly to forecast future Bitcoin prices based on historical price data. Suitable for applications like:
+- Cryptocurrency trend analysis
+- Financial planning tools
+- Educational purposes in time-series forecasting
+
+### Downstream Use
+
+The model can be fine-tuned or integrated into larger financial forecasting systems to improve predictions for related datasets.
+
+### Out-of-Scope Use
+
+- Not designed for long-term forecasting due to potential error accumulation.
+- Not suitable for non-financial time-series data without retraining.