Merge pull request #37 from IBM/ttm_preadme_fix

Ttm readme link fix

notebooks/hfdemo/tinytimemixer/ttm_pretrain_sample.py

@@ -10,6 +10,10 @@
 # Have a look at the fine-tune scripts for example usecases of the pre-trained
 # TTM models.
 
+# Basic usage:
+# python ttm_pretrain_sample.py --data_root_path datasets/
+# See the get_ttm_args() function to know more about other TTM arguments
+
 # Standard
 import math
 import os
@@ -24,8 +28,6 @@
     TinyTimeMixerConfig,
     TinyTimeMixerForPrediction,
 )
-
-# First Party
 from tsfm_public.models.tinytimemixer.utils import get_data, get_ttm_args
 
 
@@ -138,7 +140,10 @@ def pretrain(args, model, dset_train, dset_val):
 
     # Data prep
     dset_train, dset_val, dset_test = get_data(
-        args.dataset, args.context_length, args.forecast_length, data_root_path=args.data_root_path
+        args.dataset,
+        args.context_length,
+        args.forecast_length,
+        data_root_path=args.data_root_path,
     )
     print("Length of the train dataset =", len(dset_train))
 

tsfm_public/models/tinytimemixer/README.md

@@ -54,7 +54,7 @@ For Installation steps, refer [here](https://github.com/IBM/tsfm/tree/ttm)
 - Illustration notebook for 512-96 model on the considered target datasets: [here](../../../notebooks/hfdemo/tinytimemixer/ttm_benchmarking_512_96.ipynb)
 - Illustration notebook for 1024-96 model on the considered target datasets: [here](../../../notebooks/hfdemo/tinytimemixer/ttm_benchmarking_1024_96.ipynb)
 - M4-hourly transfer learning example: [here](../../../notebooks/hfdemo/tinytimemixer/ttm_m4_hourly.ipynb)
-- Sample pretraining script: [here](../../../notebooks/hfdemo/tinytimemixer/ttm_pretrain_sample.py.ipynb) 
+- Sample pretraining script: [here](../../../notebooks/hfdemo/tinytimemixer/ttm_pretrain_sample.py)