python text_parsing.py --type multimodal --benchmark_path questions.json --output_file multimodal_representations.json To conduct inverse inference about the agent's goal and belief using (finetuned) language models (taking LLaMA 2 as an example): python inverse_symbolic_planner.py --data_path...
To mark if a prompt is relevant only with a previous question or not. If true, do not include this QnA as search result for queries without context; otherwise, if false, ignores context and includes this QnA in search result. prompts prompts array of KnowledgeBaseAnswerPrompt List of pro...
public: static property Microsoft::VisualStudio::Imaging::Interop::ImageMoniker QuestionMark { Microsoft::VisualStudio::Imaging::Interop::ImageMoniker get(); }; Property Value ImageMoniker Applies to منتجالإصدارات Visual Studio SDK 2015, 2017, 2019, 2022 ف...
python ./benchmark/evaluate.py --predictions_path ./path_to_predictions/predictions.csv Download Data and Annotations The LingoQA training and evaluation datasets contain: Videos corresponding to driving scenarios Language annotations DatsetSplitVideosQA PairsQA Per ScenarioLink ...
Ask questions in natural language and find granular answers in your documents. Perform semantic search and retrieve documents according to meaning, not keywords Use off-the-shelf models or fine-tune them to your domain. Use user feedback to evaluate, benchmark, and continuously improve your live...
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• Which of these famous landmarks is not in Rome? La Sagrada Familia• Which of these is an official language of Papua New Guinea? English• Which of these latitude lines is the most northerly? Tropic of Cancer• Which of these regions is not part of the United Arab Emirates?
As MOTUs should ideally reflect species-level entities, we selected those sequences assigned at the species level as a benchmark for the MOTU datasets. We also enforced a 97% minimal best identity with the reference sequence. We traced these sequences in the output files of our procedures and...
The Stanford Question Answering Dataset (SQuAD) is a popular question answering benchmark dataset. BERT (at the time of the release) obtains state-of-the-art results on SQuAD with almost no task-specific network architecture modifications or data augmentation. However, it does require semi-complex...
backward Variable._execution_engine.run_backward( RuntimeError: Expected to mark a variable ready only once. This error is caused by one of the following reasons: 1) Use of a module parameter outside the `forward` function. Please make sure model parameters are not shared across multiple ...