YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Model Card for Model ID

This model was developed by fine-tuning [BLOOMZ-3b] (https://huggingface.co/bigscience/bloomz-3b) using the [Misconceptions] (https://huggingface.co/datasets/indikamk/misconceptions) dataset.

Model Details

Model Description

This model can be used to identify whether a sentence written by a student about an electrical circuit contains a "Sequential" Misconception.

A sequential misconception in terms of electric circuits is one in which it is believed that elements that are further “downstream” from a source “receive” current after elements closer to the source.

Uses

The model can be used to generate feedback by inputting a sentence written by a student about a simple electrical circuit The feedback would indicate whether the sentence contains a Squenctila misconception or not.

Training Details

Training Data

This model was finetuned using the [Misconceptions] (https://huggingface.co/datasets/indikamk/misconceptions) dataset.

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Dataset used to train indikamk/BLOOMZ_finetuned_Misconceptions