[docs] Add ViLT model checkpoint instructions

Add ViLT model checkpoints to model zoo.
Add ViLT finetuning and pretraining instructions
to project docs.

ghstack-source-id: 9948005
Pull Request resolved: #1161

Author: Ryan-Qiyu-Jiang

mmf/configs/zoo/models.yaml

@@ -564,3 +564,19 @@ villa:
     - url: mmf://models/uniter/villa.pretrained.tar.gz
       file_name: villa.pretrained.tar.gz
       hashcode: 7a8f31421ef644fddc99bd142a0090660573dd526a779d025253c3fd996754fc
+
+vilt:
+  defaults: ${vilt.vqa}
+  vqa:
+    # Model from project : projects/vilt, Val: 69.55
+    version: 1.0_2021_011_29
+    resources:
+    - url: mmf://models/vilt/vilt.finetuned.vqa2.tar.gz
+      file_name: vilt.finetuned.vqa2.tar.gz
+      hashcode: c1a96abfaffa140c0970592691c2cb828b3bb16be7a6c610f7d02c9c05951c1f
+  pretrained:
+    version: 1.0_2021_011_29
+    resources:
+    - url: mmf://models/vilt/vilt.pretrained.tar.gz
+      file_name: vilt.pretrained.tar.gz
+      hashcode: fb4478665ba6709bd454cec40b66dcb89570b998853745cc400bfb6f99aaeb69

website/docs/projects/vilt.md

@@ -24,9 +24,24 @@ Follow installation instructions in the [documentation](https://mmf.readthedocs.
 
 ## Training
 
-To train ViLT model on the VQA2.0 dataset, run the following command
+To train ViLT model from scratch on the VQA2.0 dataset, run the following command
 ```
 mmf_run config=projects/vilt/configs/vqa2/defaults.yaml run_type=train_val dataset=vqa2 model=vilt
 ```
 
 To finetune using different pretrained starting weights, change the `pretrained_model_name` under image_encoder in the config yaml to reference a huggingface model.
+
+To finetrain a pretrained ViLT model on the VQA2.0 dataset,
+```
+mmf_run config=projects/vilt/configs/vqa2/defaults.yaml run_type=train_val dataset=vqa2 model=vilt checkpoint.resume_zoo=vilt.pretrained
+```
+
+To test a ViLT model already finetuned on the VQA2.0 dataset,
+```
+mmf_run config=projects/vilt/configs/vqa2/defaults.yaml run_type=val dataset=vqa2 model=vilt checkpoint.resume_zoo=vilt.vqa
+```
+
+To pretrain a ViLT model from scratch on the COCO dataset,
+```
+mmf_run config=projects/vilt/configs/masked_coco/pretrain.yaml run_type=train_val dataset=masked_coco model=vilt
+```