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:
- 4c3bd76091fbc1733e9a947f0b3d72d97871d1a7dfdc976495c2a46d3959fbc3
- Size of remote file:
- 15.7 kB
- SHA256:
- 56789eee51f8d46418d8d8409c5381e9fd950c41f4aa52f0575d4b77653fee4e
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