sempl-it-v1
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Updated
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, 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
Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-mt5-small")
model = AutoModelForSeq2SeqLM.from_pretrained("VerbACxSS/sempl-it-mt5-small")
model.eval()
text_to_simplify = 'Nella fattispecie, questo documento è di natura prescrittiva'
prompt = f'semplifica: {text_to_simplify}'
x = tokenizer(prompt, max_length=1024, truncation=True, padding=True, return_tensors='pt').input_ids
y = model.generate(x, max_length=1024)[0]
output = tokenizer.decode(y, max_length=1024, truncation=True, skip_special_tokens=True, clean_up_tokenization_spaces=True)
print(output)
Acknowledgements
This contribution is a result of the research conducted within the framework of the PRIN 2020 (Progetti di Rilevante Interesse Nazionale) "VerbACxSS: on analytic verbs, complexity, synthetic verbs, and simplification. For accessibility" (Prot. 2020BJKB9M), funded by the Italian Ministero dell'Università e della Ricerca.
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Model tree for VerbACxSS/sempl-it-mt5-small
Base model
google/mt5-small