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")# 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 pytorch_model.bin from staka/fugumt-en-ja: direct link, hf CLI and curl.
- Browser
- Download file 121 MB
-
https://huggingface.co/staka/fugumt-en-ja/resolve/refs%2Fpr%2F4/pytorch_model.bin
- Command line
-
hf download hf://staka/fugumt-en-ja@refs/pr/4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/staka/fugumt-en-ja/resolve/refs%2Fpr%2F4/pytorch_model.bin
121 MB
- Xet hash:
- bef90430906830a1a43c1dc36d0a17b19172f3fce3001fe13c52142e9d7f103c
- Size of remote file:
- 121 MB
- SHA256:
- 8b2d3d3b7da2f66dfd46187646dd1ea48918e9a5406f0153c497478432425fe8
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