Instructions to use doc2query/msmarco-vietnamese-mt5-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use doc2query/msmarco-vietnamese-mt5-base-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("doc2query/msmarco-vietnamese-mt5-base-v1") model = AutoModelForSeq2SeqLM.from_pretrained("doc2query/msmarco-vietnamese-mt5-base-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from doc2query/msmarco-vietnamese-mt5-base-v1: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/doc2query/msmarco-vietnamese-mt5-base-v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://doc2query/msmarco-vietnamese-mt5-base-v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/doc2query/msmarco-vietnamese-mt5-base-v1/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- cf8f5774121b228497949523f2031b75b21b7d619421d26631d082b7aa2bbfff
- Size of remote file:
- 2.33 GB
- SHA256:
- 57ff34123aa553a2a0ad51eb25a491c3411ba23a4e8a84828e50a42ce521e368
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.