Instructions to use WindyTranslate/translate-bem-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-bem-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-bem-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-bem-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-bem-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download source.spm from WindyTranslate/translate-bem-es: direct link, hf CLI and curl.
- Browser
- Download file 832 kB
-
https://huggingface.co/WindyTranslate/translate-bem-es/resolve/main/source.spm
- Command line
-
hf download hf://WindyTranslate/translate-bem-es/source.spm
-
curl -L -o source.spm https://huggingface.co/WindyTranslate/translate-bem-es/resolve/main/source.spm
832 kB
- Xet hash:
- fbfbc93ce28e69316fe66665da86c6dee8847216de494c7d3756784ce461b70f
- Size of remote file:
- 832 kB
- SHA256:
- a3423b4499dfd5d01424bb9a80e57c7b13c51fc054d9cf4665b99aa8a176ef61
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