Instructions to use ainewtrend07/google-mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ainewtrend07/google-mt5-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ainewtrend07/google-mt5-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ainewtrend07/google-mt5-base") model = AutoModelForSequenceClassification.from_pretrained("ainewtrend07/google-mt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ainewtrend07/google-mt5-base: direct link, hf CLI and curl.
- Browser
- Download file 16.4 MB
-
https://huggingface.co/ainewtrend07/google-mt5-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://ainewtrend07/google-mt5-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ainewtrend07/google-mt5-base/resolve/main/tokenizer.json
16.4 MB
- Xet hash:
- 081f0fb3dbaf0345c821d8b686bbdfbfabf979cd6e2aa3b0f397e2f3479e3cc2
- Size of remote file:
- 16.4 MB
- SHA256:
- 4ee250577819245cd7d577250e79fc930a1754d4ccf63bb012a082d6ab28a100
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