Instructions to use obokkkk/mt5-base_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use obokkkk/mt5-base_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("obokkkk/mt5-base_2") model = AutoModelForSeq2SeqLM.from_pretrained("obokkkk/mt5-base_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from obokkkk/mt5-base_2: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/obokkkk/mt5-base_2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://obokkkk/mt5-base_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/obokkkk/mt5-base_2/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- 5b25d984e52dc6d6ba1a6cad31365f265b2f3686540fca14d98dc85f32b1dd31
- Size of remote file:
- 2.33 GB
- SHA256:
- d15a184bcc0d48ea71772e2fb87492505e4b179d29680af9cdd40d62473380ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.