Instructions to use WindyTranslate/translate-nso-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-nso-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-nso-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-nso-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-nso-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-nso-es, with attribution and change statement
7c04b1a verified - Xet hash:
- 98a7d0d85e4dcf86f380834efd19f15b0df8ac2f59fda1fe750340c3ac0e6e8e
- Size of remote file:
- 824 kB
- SHA256:
- 41cf47880aec5d4dc64ab4b3a1ff5d15507fb9f68038a70378ad757b04b81b0b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.