Instructions to use WindyTranslate/translate-fr-ms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-fr-ms 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-fr-ms")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-fr-ms") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-fr-ms", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download source.spm from WindyTranslate/translate-fr-ms: direct link, hf CLI and curl.
- Browser
- Download file 823 kB
-
https://huggingface.co/WindyTranslate/translate-fr-ms/resolve/main/source.spm
- Command line
-
hf download hf://WindyTranslate/translate-fr-ms/source.spm
-
curl -L -o source.spm https://huggingface.co/WindyTranslate/translate-fr-ms/resolve/main/source.spm
823 kB
- Xet hash:
- 1738c60935ff87186eb187e70d2668429a8d4b6e3b870a5a2e3f67a95943f34e
- Size of remote file:
- 823 kB
- SHA256:
- 7470ad11bf8855b132e56b9bf1e8a84e2b2b617b352920a189f5fd24c16c2672
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.