Instructions to use Language-Media-Lab/mt5-small-ain-jpn-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Language-Media-Lab/mt5-small-ain-jpn-mt 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="Language-Media-Lab/mt5-small-ain-jpn-mt")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Language-Media-Lab/mt5-small-ain-jpn-mt") model = AutoModelForSeq2SeqLM.from_pretrained("Language-Media-Lab/mt5-small-ain-jpn-mt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from Language-Media-Lab/mt5-small-ain-jpn-mt: direct link, hf CLI and curl.
- Browser
- Download file 14.5 kB
-
https://huggingface.co/Language-Media-Lab/mt5-small-ain-jpn-mt/resolve/main/rng_state.pth
- Command line
-
hf download hf://Language-Media-Lab/mt5-small-ain-jpn-mt/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Language-Media-Lab/mt5-small-ain-jpn-mt/resolve/main/rng_state.pth
14.5 kB
- Xet hash:
- 0c68df5c89f0a9156cdf7d82aadab8442f539ebb35c48bebdc923d9c684f7491
- Size of remote file:
- 14.5 kB
- SHA256:
- 2fa6d6acba3a387a74e2512985fef7c05af9eabbf101c09cc8394722cbd9e922
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