Instructions to use staka/fugumt-en-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use staka/fugumt-en-ja 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="staka/fugumt-en-ja")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("staka/fugumt-en-ja") model = AutoModelForSeq2SeqLM.from_pretrained("staka/fugumt-en-ja", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from staka/fugumt-en-ja: direct link, hf CLI and curl.
- Browser
- Download file 42 Bytes
-
https://huggingface.co/staka/fugumt-en-ja/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://staka/fugumt-en-ja/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/staka/fugumt-en-ja/resolve/main/tokenizer_config.json
42 Bytes
| {"target_lang": "ja", "source_lang": "en"} |