Transformers
PyTorch
t5
text2text-generation
text-2-text-generation
augmentation
paraphrase
paraphrasing
text-generation-inference
Instructions to use ibm-research/qcpg-sentences with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/qcpg-sentences with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ibm-research/qcpg-sentences") model = AutoModelForSeq2SeqLM.from_pretrained("ibm-research/qcpg-sentences", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40ab1aada2c36293c8349df60f011a46429f15fffc68e78fec34b4dfcfab8715
- Size of remote file:
- 892 MB
- SHA256:
- 01d55465d5cb84ab252a682249e96a80d37f18edc2345c8e8d54638b0f1bbdea
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