Instructions to use WindyTranslate/translate-tzo-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-tzo-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-tzo-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-tzo-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-tzo-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-tzo-es, with attribution and change statement
4ad6601 verified - Xet hash:
- 11d391c47b37043b2353cc55e165c4382c5e5400d1666bde588420bbb459acb1
- Size of remote file:
- 750 kB
- SHA256:
- 6ed78dfd363579ae7416ca11093d96d8f1777e5708f914b1dad48497eeff5943
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.