Instructions to use beatrice12/mt5-small-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beatrice12/mt5-small-all with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("beatrice12/mt5-small-all") model = AutoModelForSeq2SeqLM.from_pretrained("beatrice12/mt5-small-all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from beatrice12/mt5-small-all: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/beatrice12/mt5-small-all/resolve/main/tokenizer.json
- Command line
-
hf download hf://beatrice12/mt5-small-all/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/beatrice12/mt5-small-all/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 6592f8708da78108d5232b7410e9aec1783ccc9ce6ff19d172217ecea65458c7
- Size of remote file:
- 16.3 MB
- SHA256:
- 8b82b393588c97ef92eaedfe1c6f7adf4795a4c945f513791e30cc6b6a4510c5
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