Instructions to use phuvo05/En-Vi-Neural-Machine-Translation-using-Transformers-based with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phuvo05/En-Vi-Neural-Machine-Translation-using-Transformers-based with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("phuvo05/En-Vi-Neural-Machine-Translation-using-Transformers-based", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from phuvo05/En-Vi-Neural-Machine-Translation-using-Transformers-based: direct link, hf CLI and curl.
- Browser
- Download file 281 Bytes
-
https://huggingface.co/phuvo05/En-Vi-Neural-Machine-Translation-using-Transformers-based/resolve/main/config.json
- Command line
-
hf download hf://phuvo05/En-Vi-Neural-Machine-Translation-using-Transformers-based/config.json
-
curl -L -o config.json https://huggingface.co/phuvo05/En-Vi-Neural-Machine-Translation-using-Transformers-based/resolve/main/config.json
281 Bytes
| { | |
| "architectures": [ | |
| "Seq2SeqTransformerModel" | |
| ], | |
| "d_model": 256, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "max_seq_length": 75, | |
| "num_heads": 8, | |
| "num_layers": 6, | |
| "transformers_version": "5.1.0", | |
| "vocab_size_src": 15000, | |
| "vocab_size_tgt": 13684 | |
| } | |