DarthReca commited on
Commit
f9321f9
·
verified ·
1 Parent(s): b3520c0

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +3 -3
README.md CHANGED
@@ -18,13 +18,13 @@ library_name: transformers
18
  # ACTU for Magnitude Regression
19
 
20
  <!-- Provide a quick summary of what the model is/does. -->
21
- This is ACTU for pixelwise regression of MNDWI.
22
 
23
  ## Model Details
24
 
25
  <!-- Provide a longer summary of what this model is. -->
26
  This architecture is a temporal UNet (with ConvLSTMs), featuring an LSTM branch to process climate timeseries and a gating mechanism.
27
- It is designed to receive a timeseries of Sentinel-2 images, DEM, and timeseries of climate variables and output a single real mask of future MNDWI.
28
 
29
  - **Developed by:** Daniele Rege Cambrin
30
  - **Model type:** ACTU
@@ -37,7 +37,7 @@ It is designed to receive a timeseries of Sentinel-2 images, DEM, and timeseries
37
  The model is integrated into Transformers, so you can easily load it with the following code:
38
 
39
  ```python
40
- AutoModel.from_pretrained("DarthReca/actu-magnitude-regression", trust_remote_code=True, revision=<model_type>)
41
  ```
42
 
43
  Load the model with the desired configuration with the *revision* parameter (the branches of this repo). These configurations are available:
 
18
  # ACTU for Magnitude Regression
19
 
20
  <!-- Provide a quick summary of what the model is/does. -->
21
+ This is ACTU for direction classification of MNDWI difference.
22
 
23
  ## Model Details
24
 
25
  <!-- Provide a longer summary of what this model is. -->
26
  This architecture is a temporal UNet (with ConvLSTMs), featuring an LSTM branch to process climate timeseries and a gating mechanism.
27
+ It is designed to receive a timeseries of Sentinel-2 images, DEM, and timeseries of climate variables and output a tri-class mask of future MNDWI direction of change.
28
 
29
  - **Developed by:** Daniele Rege Cambrin
30
  - **Model type:** ACTU
 
37
  The model is integrated into Transformers, so you can easily load it with the following code:
38
 
39
  ```python
40
+ AutoModel.from_pretrained("DarthReca/actu-direction-classification", trust_remote_code=True, revision=<model_type>)
41
  ```
42
 
43
  Load the model with the desired configuration with the *revision* parameter (the branches of this repo). These configurations are available: