Instructions to use lewtun/tiny-random-mt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lewtun/tiny-random-mt5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lewtun/tiny-random-mt5")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lewtun/tiny-random-mt5") model = AutoModel.from_pretrained("lewtun/tiny-random-mt5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02eb830962c20aba366e3e66ad14a54dafb24643d2a31f9263eab5516e373364
- Size of remote file:
- 18.1 MB
- SHA256:
- f39c5e49cec195a636018581dd12de3b9a0d33f8bc791d3650073a41a17ac512
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