Transformers
PyTorch
Chinese
t5
text2text-generation
conditional text generation
data augmentation
text-generation-inference
Instructions to use Maciel/T5_Mask_Completion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maciel/T5_Mask_Completion with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Maciel/T5_Mask_Completion") model = AutoModelForSeq2SeqLM.from_pretrained("Maciel/T5_Mask_Completion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ac880a2a3efec817eec6e06118d6699b42a8c58429147918f3e3e604483e43b
- Size of remote file:
- 990 MB
- SHA256:
- da415169808b16bd4418b65c87893c57449ad95aa788ce81c7567af942f3a4a8
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