Instructions to use WindyTranslate/translate-mt-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-mt-es 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="WindyTranslate/translate-mt-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-mt-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-mt-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote herm0 build from WindstormLabs/translate-mt-es, with attribution and change statement
d494a0c verified Download source.spm from WindyTranslate/translate-mt-es: direct link, hf CLI and curl.
- Browser
- Download file 791 kB
-
https://huggingface.co/WindyTranslate/translate-mt-es/resolve/main/source.spm
- Command line
-
hf download hf://WindyTranslate/translate-mt-es/source.spm
-
curl -L -o source.spm https://huggingface.co/WindyTranslate/translate-mt-es/resolve/main/source.spm
791 kB
- Xet hash:
- 9d4888d6f238a554eaa14264d8725c424097189de1eaa3aee61793a246e549a1
- Size of remote file:
- 791 kB
- SHA256:
- 621554749f7f1fe47e1025d5c0d1947560721731acb1b0d091a757555f7a9920
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