videomae-base-Vsl-Lab-PC-V9

# Ejemplo de uso del modelo
from transformers import VideoMaeForVideoClassification, VideoMaeFeatureExtractor
import torch

# Cargar el modelo y el extractor de características
model = VideoMaeForVideoClassification.from_pretrained('Ham1mad1/videomae-base-Vsl-Lab-PC-V9')
feature_extractor = VideoMaeFeatureExtractor.from_pretrained('Ham1mad1/videomae-base-Vsl-Lab-PC-V9')

# Preparar el video de entrada
video_path = 'ruta/al/video.mp4'
inputs = feature_extractor([video_path], return_tensors="pt")

# Realizar la clasificación de video
with torch.no_grad():
    outputs = model(**inputs)
    logits = outputs.logits

# Obtener el resultado
predicted_class = torch.argmax(logits, dim=-1)
print(f'Clase predicha: {predicted_class}')