Instructions to use WindyTranslate/translate-tr-az with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-tr-az 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-tr-az")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-tr-az") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-tr-az", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote herm0 build from WindstormLabs/translate-tr-az, with attribution and change statement
3d6b83d verified - Xet hash:
- 84177680a08b14875c704d8fc29a8ef1ddffbdc2f73aac87d228fc27fa7cffc6
- Size of remote file:
- 306 kB
- SHA256:
- df02a7653d1441aa3f771bade2cbc0ab81d4cbaeb60088bb073935b2172f3918
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.