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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, 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
ruT5 Keyphrase Generator (Russian)
Base model: sberbank-ai/ruT5-base
Dataset: aglazkova/keyphrase_extraction_russian
Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tok = AutoTokenizer.from_pretrained("denis-gordeev/rut5-keyphrase-ru", use_fast=False)
mdl = AutoModelForSeq2SeqLM.from_pretrained("denis-gordeev/rut5-keyphrase-ru")
text = "keyphrase: Новая модель обнаруживает аномалии в банковских транзакциях..."
inp = tok(text, return_tensors="pt")
out = mdl.generate(**inp, max_new_tokens=64, num_beams=4, no_repeat_ngram_size=3)
print(tok.decode(out[0], skip_special_tokens=True))
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Model tree for denis-gordeev/rut5-keyphrase
Base model
ai-forever/ruT5-baseDataset used to train denis-gordeev/rut5-keyphrase
Evaluation results
- rougeL on aglazkova/keyphrase_extraction_russianself-reported0.XX
- exact_match on aglazkova/keyphrase_extraction_russianself-reported0.XX