Detector model (opens in a new window) Model card (opens in a new window) As the final model release of GPT-2’s staged release, we’re releasing the largest version (1.5B parameters) of GPT-2 along with code and model weights(opens in a new window) to facilitate detection...
detector model Nov 6, 2019 README MIT license gpt-2-output-dataset This dataset contains: 250K documents from the WebText test set For each GPT-2 model (trained on the WebText training set), 250K random samples (temperature 1, no truncation) and 250K samples generated with Top-K 40 tr...
We’ve fine-tuned the 774M parameter GPT-2 language model using human feedback for various tasks, successfully matching the preferences of the external human labelers, though those preferences did not always match our own. Specifically, for summarization tasks the labelers preferred sentences copied...
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Introducing the GPT Store Research Your browser does not support the video tag. Research Feb 2, 2025 Introducing deep research Your browser does not support the video tag. Research Jan 31, 2025 Introducing OpenAI o3-mini Safety & Alignment ...
https://github.com/openai/gpt-2-output-dataset/tree/master/detector 1.5B模型评分优于其他尺寸模型 OpenAI在康奈尔大学(Cornell University)的工作人员让人们对不同模型尺寸下的GPT-2文本的可信度进行评分。 1.5B模型的“可信度评分”是6.91分(满分10分),略大于774M模型的6.72分,显著高于355M模型的6.07分。根据...
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GPT-2 models' robustness and worst case behaviors are not well-understood. As with any machine-learned model, carefully evaluate GPT-2 for your use case, especially if used without fine-tuning or in safety-critical applications where reliability is important. ...
Breadcrumbs gpt-2-output-dataset /detector / dataset.pyTop File metadata and controls Code Blame 86 lines (69 loc) · 3.47 KB Raw import json import numpy as np from typing import List import torch from torch.utils.data import Dataset from tqdm import tqdm from transformers impor...