Instructions to use WindyTranslate/translate-sv-ny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-ny 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-ny")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-ny") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-ny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-ny, with attribution and change statement
27d369a verified - Xet hash:
- 0dddb457b4f73c908ce8f8232c767687a79012420ce626ba03ab171a5333b179
- Size of remote file:
- 854 kB
- SHA256:
- 62a1eeed9abeefe9697bc314990e448cbb0b98a079f5a1616646e61f5c165c10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.