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:
- 36eb8f04edf0a0846b16c7eed31cfc5e4b65c2e98d91c91d01a7b755fbac2bbf
- Size of remote file:
- 2.33 GB
- SHA256:
- f6aa98be27bb19b452f6f23feacda0b3ddfce9bd2c4778e40e6b8a4807b23c47
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