Instructions to use Atnafu/mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atnafu/mt5-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Atnafu/mt5-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Atnafu/mt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("Atnafu/mt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91a5952e6271c38def2b6b934b902d3827243d89b5726b6cee5916bccbca61dc
- Size of remote file:
- 3.71 kB
- SHA256:
- 34838a9c1b6895196539279b4f8585dfadae49ba522449c2d0a51f014d1eb090
路
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