Instructions to use tharindu/mt5_0.1SOLID_CCTK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tharindu/mt5_0.1SOLID_CCTK with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tharindu/mt5_0.1SOLID_CCTK") model = AutoModelForSeq2SeqLM.from_pretrained("tharindu/mt5_0.1SOLID_CCTK", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8987032b42fecf9fc961ff3c771c21508ba0d186cf5dc09fe1a451d0d710ff8c
- Size of remote file:
- 4.11 MB
- SHA256:
- 11c5eddac738585b23e66355f5d63aed2cc8a005fc1b97e1e358877ef834e953
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