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 pytorch_model.bin from whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521/resolve/ff0c959df685325ee755a633da324c37c081a105/pytorch_model.bin
- Command line
-
hf download hf://whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521@ff0c959df685325ee755a633da324c37c081a105/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521/resolve/ff0c959df685325ee755a633da324c37c081a105/pytorch_model.bin
1.2 GB
- Xet hash:
- b3f3b59ad46f5212bcdc699c941a1827673ac86dc4ac255da2e8968f1cc0a8b4
- Size of remote file:
- 1.2 GB
- SHA256:
- 2468264674523e9c2a00b2972337806aa108ae05577234f678eea831f7150af3
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