Update README.md

README.md

@@ -5,4 +5,70 @@ base_model:
 - Salesforce/moirai-1.0-R-base
 - Salesforce/moirai-1.0-R-large
 pipeline_tag: time-series-forecasting
----
+---
+
+---
+license: cc-by-nc-nd-4.0
+base_model:
+- Salesforce/moirai-1.0-R-small
+- Salesforce/moirai-1.0-R-base
+- Salesforce/moirai-1.0-R-large
+pipeline_tag: time-series-forecasting
+---
+
+
+# Time Series Forecasting Model
+
+This model is built on top of the Salesforce Moirai architecture, specifically fine-tuned and trained from scratch for time series forecasting tasks.
+
+## Model Details
+
+### Model Description
+
+This model leverages the Moirai architecture from Salesforce, which is designed specifically for time series forecasting. The model is available in multiple versions:
+
+- Fine-tuned variants (located in `./finetune` directory)
+- Trained from scratch variants (located in `./train_from_scratch` directory)
+
+All checkpoint files (.ckpt) include self-explanatory naming conventions that indicate their configuration and training approach.
+
+### Model Type
+
+Time Series Forecasting
+
+### Version
+
+1.0
+
+
+## Training Procedure
+
+### Training Methodology
+
+Two distinct training approaches were utilized:
+1. **Fine-tuning approach**: Starting with the pre-trained Moirai models (small, base) and fine-tuning on domain-specific data
+2. **Training from scratch**: Building models with the Moirai architecture but training entirely on specific datasets
+
+
+## Limitations and Biases
+
+- The model inherits any limitations present in the base Moirai architecture
+- Performance may degrade for extremely long-range forecasts
+- The model may not perform optimally on domains significantly different from its training data
+
+## Additional Information
+
+### Checkpoints
+
+The model checkpoints are organized as follows:
+- Fine-tuned models: `./finetune/*.ckpt`
+- Models trained from scratch: `./train_from_scratch/*.ckpt`
+
+
+### Citation
+
+If you use this model in your research, please cite: TBA
+
+### License
+
+This model is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).