Translation
Transformers
PyTorch
ONNX
Safetensors
Japanese
English
encoder-decoder
text2text-generation
Instructions to use sappho192/jesc-ja-en-translator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sappho192/jesc-ja-en-translator with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="sappho192/jesc-ja-en-translator")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sappho192/jesc-ja-en-translator") model = AutoModelForSeq2SeqLM.from_pretrained("sappho192/jesc-ja-en-translator") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62c34e403b9094ff9b790fe5f0ac5fad073ef21340d16e4cae7f6aa99d4a7f0c
- Size of remote file:
- 1.08 GB
- SHA256:
- ba66bd4883ae443b3c378ddb83d4a56b72d158ca3e9df754faedeb8ee31f5064
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