Instructions to use msbayindir/mt5_small_50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msbayindir/mt5_small_50 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("msbayindir/mt5_small_50") model = AutoModelForSeq2SeqLM.from_pretrained("msbayindir/mt5_small_50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from msbayindir/mt5_small_50: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/msbayindir/mt5_small_50/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://msbayindir/mt5_small_50/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/msbayindir/mt5_small_50/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- 5eec9fc2e10a5ee15312c08da78c01cc3b1acfc3849248e7c8de40e4bc6b751c
- Size of remote file:
- 1.2 GB
- SHA256:
- b29c5b589a4a26f3d07adc98a480e9a039aa0e08f59e0fdb3d2049129713b552
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