update links

README.md

@@ -20,8 +20,8 @@ This repository contains pretrained model for Gravity Wave Flux Parametrization
 
 
 ### Model
-The pretrained [Prithvi WxC](https://huggingface.co/Prithvi-WxC/prithvi.wxc.2300m.v1) parameter model is finetuned to predict momentum fluxes from
-the [Gravity Wave Parameterization dataset](https://huggingface.co/datasets/Prithvi-WxC/Gravity_wave_Parameterization).
+The pretrained [Prithvi WxC](https://huggingface.co/ibm-nasa-geospatial/Prithvi-WxC-1.0-2300M) parameter model is finetuned to predict momentum fluxes from
+the [Gravity Wave Parameterization dataset](https://huggingface.co/datasets/ibm-nasa-geospatial/gravity-wave-parameterization).
 
 <b>Input:</b> 491 (3 + 4x122) channels. 
 1. latitude (1)
@@ -49,8 +49,8 @@ the fine-tuned model achieves correlation coefficients of 0.99 and 0.97, respect
 
 ### Inference and demo
 The github repo includes an inference script that allows to run 
-the [gravity_wave_model](https://huggingface.co/Prithvi-WxC/Gravity_wave_Parameterization/blob/main/magnet-flux-uvtp122-epoch-99-loss-0.1022.pt) model 
-for inference on [sample dataset](https://huggingface.co/datasets/Prithvi-WxC/Gravity_wave_Parameterization/blob/main/wxc_input_u_v_t_p_output_theta_uw_vw_era5_training_data_hourly_2015_constant_mu_sigma_scaling05.nc).
+the [gravity_wave_model](https://huggingface.co/ibm-nasa-geospatial/Prithvi-WxC-1.0-2300m-gravity-wave-parameterization/blob/main/magnet-flux-uvtp122-epoch-99-loss-0.1022.pt) model 
+for inference on [sample dataset](https://huggingface.co/datasets/ibm-nasa-geospatial/gravity-wave-parameterization/blob/main/wxc_input_u_v_t_p_output_theta_uw_vw_era5_training_data_hourly_2015_constant_mu_sigma_scaling05.nc).
 
 ## Citation
 If you use this work, consider citing our paper