Instructions to use Davlan/mt5-small-en-pcm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/mt5-small-en-pcm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Davlan/mt5-small-en-pcm") model = AutoModelForSeq2SeqLM.from_pretrained("Davlan/mt5-small-en-pcm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Davlan/mt5-small-en-pcm: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/Davlan/mt5-small-en-pcm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Davlan/mt5-small-en-pcm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Davlan/mt5-small-en-pcm/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- 0dad070775cbc089c72fe5779d036b5833c47af6b9f2a63b3674e341d8322a36
- Size of remote file:
- 1.2 GB
- SHA256:
- e24a3b24afa6ada57c4df2def956832d4cf338fbc1ad770d68bb6d4750f3aff4
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