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:
# pip install -U transformers accelerate # 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 training_args.bin from whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521: direct link, hf CLI and curl.
- Browser
- Download file 3.5 kB
-
https://huggingface.co/whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521/resolve/b444890aed28618f74db07763e3283b1a77bc260/training_args.bin
- Command line
-
hf download hf://whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521@b444890aed28618f74db07763e3283b1a77bc260/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/whatdhack/mt5-small-finetuned-amazon-en-es-20220901_001521/resolve/b444890aed28618f74db07763e3283b1a77bc260/training_args.bin
3.5 kB
- Xet hash:
- db69b6ad8928b9930c251fa175fa6ac1050373d7bb67c7c821f374bcefe0071f
- Size of remote file:
- 3.5 kB
- SHA256:
- 2e32f01e0d831f9ddf7abf187b095fa28715ee9c32bff2b23f9f35336626c38c
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