Instructions to use whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521") model = AutoModelForSeq2SeqLM.from_pretrained("whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521/resolve/b444890aed28618f74db07763e3283b1a77bc260/tokenizer.json
- Command line
-
hf download hf://whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521@b444890aed28618f74db07763e3283b1a77bc260/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521/resolve/b444890aed28618f74db07763e3283b1a77bc260/tokenizer.json
16.3 MB
- Xet hash:
- 2e85b266d33e9326b5a2ad2f010223225ac7105e9aac29eb8d0d9e1292c13fe6
- Size of remote file:
- 16.3 MB
- SHA256:
- 93c3578052e1605d8332eb961bc08d72e246071974e4cc54aa6991826b802aa5
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