Instructions to use staka/fugumt-ja-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use staka/fugumt-ja-en 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-ja-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("staka/fugumt-ja-en") model = AutoModelForSeq2SeqLM.from_pretrained("staka/fugumt-ja-en", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from staka/fugumt-ja-en: direct link, hf CLI and curl.
- Browser
- Download file 121 MB
-
https://huggingface.co/staka/fugumt-ja-en/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://staka/fugumt-ja-en/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/staka/fugumt-ja-en/resolve/main/pytorch_model.bin
121 MB
- Xet hash:
- a03bb593b7aee4c40cfcd9c8dee05caedeb4784c5b4dfae60aa44b0c737b1c5a
- Size of remote file:
- 121 MB
- SHA256:
- 3e15d0b016255711ef06a3740933c3fa9eb7609a9c3e99d5326fbc7872a13729
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.