Update README.md

README.md

@@ -5,7 +5,7 @@ tags:
 - video-classification
 ---
 
-# TimeSformer (base-sized model, fine-tuned on Something Something v2) 
+# TimeSformer (high-resolution variant, fine-tuned on Something Something v2) 
 
 TimeSformer model pre-trained on [Something Something v2](https://developer.qualcomm.com/software/ai-datasets/something-something). It was introduced in the paper [TimeSformer: Is Space-Time Attention All You Need for Video Understanding?](https://arxiv.org/abs/2102.05095) by Tong et al. and first released in [this repository](https://github.com/facebookresearch/TimeSformer). 
 
@@ -24,12 +24,12 @@ from transformers import AutoImageProcessor, TimesformerForVideoClassification
 import numpy as np
 import torch
 
-video = list(np.random.randn(8, 3, 224, 224))
+video = list(np.random.randn(16, 3, 448, 448))
 
-processor = AutoImageProcessor.from_pretrained("fcakyon/timesformer-base-finetuned-ssv2")
-model = TimesformerForVideoClassification.from_pretrained("fcakyon/timesformer-base-finetuned-ssv2")
+processor = AutoImageProcessor.from_pretrained("fcakyon/timesformer-hr-finetuned-ssv2")
+model = TimesformerForVideoClassification.from_pretrained("fcakyon/timesformer-hr-finetuned-ssv2")
 
-inputs = processor(images=video, return_tensors="pt")
+inputs = feature_extractor(images=video, return_tensors="pt")
 
 with torch.no_grad():
   outputs = model(**inputs)