Update README.md

README.md

@@ -4,6 +4,8 @@ pipeline_tag: video-classification
 tags:
 - video
 library_name: transformers
+datasets:
+- bkprocovid19/diving48
 ---
 
 # V-JEPA 2
@@ -44,7 +46,7 @@ model = AutoModelForVideoClassification.from_pretrained(hf_repo).to(device)
 processor = AutoVideoProcessor.from_pretrained(hf_repo)
 
 # To load a video, sample the number of frames according to the model.
-video_url = "converted_models/vjepa2-vitg-fpc32-384-diving48/sample/diving.mp4" #"https://huggingface.co/datasets/nateraw/kinetics-mini/resolve/main/val/bowling/-WH-lxmGJVY_000005_000015.mp4"
+video_url = "https://huggingface.co/qubvel-hf/vjepa2-vitl-fpc32-256-diving48/resolve/main/sample/diving.mp4"
 vr = VideoDecoder(video_url)
 frame_idx = np.arange(0, model.config.frames_per_clip, 8) # you can define more complex sampling strategy
 video = vr.get_frames_at(indices=frame_idx).data  # frames x channels x height x width