Instructions to use ikala-ray/mt5-small-trim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ikala-ray/mt5-small-trim with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ikala-ray/mt5-small-trim") model = AutoModelForSeq2SeqLM.from_pretrained("ikala-ray/mt5-small-trim", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ikala-ray/mt5-small-trim: direct link, hf CLI and curl.
- Browser
- Download file 7.23 MB
-
https://huggingface.co/ikala-ray/mt5-small-trim/resolve/main/tokenizer.json
- Command line
-
hf download hf://ikala-ray/mt5-small-trim/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/ikala-ray/mt5-small-trim/resolve/main/tokenizer.json
7.23 MB
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