Instructions to use WindyTranslate/translate-sv-no with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-no 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-sv-no")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-no") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-no", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote herm0 build from WindstormLabs/translate-sv-no, with attribution and change statement
cd031a6 verified - Xet hash:
- c1fd5a2dd15d962acb2d2ac432bacf0409e083fa2ac7f02eba4ad50595b01b61
- Size of remote file:
- 304 kB
- SHA256:
- 7372d40652b9088539d8987985fb3a760b163f3b896203560ddeb6866a1ab81a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.