Update README.md

README.md

@@ -71,6 +71,45 @@ getting started [notebook](https://github.com/IBM/tsfm/blob/main/notebooks/hfdem
     in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
     resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 1536-96-r2) [[Benchmarks]](https://github.com/ibm-granite/granite-tsfm/blob/main/notebooks/hfdemo/tinytimemixer/ttm-r2_benchmarking_1536_96.ipynb)
 
+
+- **512-192-r2**: Given the last 512 time-points (i.e. context length), this model can forecast up to next 192 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 512-192-r2) 
+  
+- **1024-192-r2**: Given the last 1024 time-points (i.e. context length), this model can forecast up to next 192 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 1024-192-r2) 
+
+- **1536-192-r2**: Given the last 1536 time-points (i.e. context length), this model can forecast up to next 192 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 1536-192-r2)
+
+  
+- **512-336-r2**: Given the last 512 time-points (i.e. context length), this model can forecast up to next 336 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 512-336-r2) 
+  
+- **1024-336-r2**: Given the last 1024 time-points (i.e. context length), this model can forecast up to next 336 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 1024-336-r2) 
+
+- **1536-336-r2**: Given the last 1536 time-points (i.e. context length), this model can forecast up to next 336 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 1536-336-r2)
+
+
+  
+- **512-720-r2**: Given the last 512 time-points (i.e. context length), this model can forecast up to next 720 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 512-720-r2) 
+  
+- **1024-720-r2**: Given the last 1024 time-points (i.e. context length), this model can forecast up to next 720 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 1024-720-r2) 
+
+- **1536-720-r2**: Given the last 1536 time-points (i.e. context length), this model can forecast up to next 720 time-points (i.e. forecast length)
+    in future. This model is pre-trained with a larger pretraining dataset for improved accuracy. Recommended for hourly and minutely
+    resolutions (Ex. 10 min, 15 min, 1 hour, etc).   (branch name: 1536-720-r2) 
     
 
 ## Model Capabilities with example scripts