Instructions to use X-Wang/pruned-mt5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use X-Wang/pruned-mt5-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("X-Wang/pruned-mt5-small") model = AutoModelForSeq2SeqLM.from_pretrained("X-Wang/pruned-mt5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from X-Wang/pruned-mt5-small: direct link, hf CLI and curl.
- Browser
- Download file 2.85 MB
-
https://huggingface.co/X-Wang/pruned-mt5-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://X-Wang/pruned-mt5-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/X-Wang/pruned-mt5-small/resolve/main/tokenizer.json
2.85 MB
- Xet hash:
- 9bd816a9ed9c262de1c331b2716e40286395386f799e9ca5204c73a4ce50e274
- Size of remote file:
- 2.85 MB
- SHA256:
- aed4b57ade9307756077e2343a25c2fa498b176d3803dd362d0214c6c48b145f
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