{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[{"file_id":"1PtimiIJM285j9vE-eUQLPGv_uwKtkWjV","timestamp":1753460744468}],"authorship_tag":"ABX9TyN7ceYXsJzN2dY1FTo5KMoK"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","source":["# @markdown Import list of all Tensor Art posts as 150Mb size .parquet file (SFW only)\n","!pip install -U datasets\n","from datasets import load_dataset\n","ds = load_dataset(\"bigdata-pw/tensorart\")\n"],"metadata":{"id":"ZwwIE7dBOGtt"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# @markdown Browse images on Tensor Art (SFW only)\n","# @markdown
Index = 1000*K+N\n","# Example: Access the first item in the dataset (adjust based on dataset structure)\n","\n","from IPython.display import Image, display\n","K= 137 # @param {type:'slider',min:0,max:270}\n","start_at_K = K\n","N = 50 # @param {type:'slider',min:0,max:999}\n","start_at = N\n","travel = 100 # How far we will travel down list in case of misses\n","url =''\n","START_AT = 1000*start_at_K+start_at\n","for index in range(START_AT+travel):\n"," if index"],"text/plain":[""]},"metadata":{}}]}]}