Instructions to use FiveC/EDA_RI-Vie-Bahnar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FiveC/EDA_RI-Vie-Bahnar with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FiveC/EDA_RI-Vie-Bahnar") model = AutoModelForSeq2SeqLM.from_pretrained("FiveC/EDA_RI-Vie-Bahnar") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 722825b55fa60d38cbb8681d55c3ea8e076aae1c9e393c2d6c8e4c14c0a99d69
- Size of remote file:
- 1.58 GB
- SHA256:
- ca7a7b902befc27588afa2da9b421f55dc2445a5d1a5ea1115ee545a7f9bd99b
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