Instructions to use WindyTranslate/translate-pon-fi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-pon-fi 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-pon-fi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-pon-fi") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-pon-fi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-pon-fi, with attribution and change statement
d787dbc verified - Xet hash:
- 20621bd108295d34fac66188ccee2fde89b6fe0a99f5bb82217a1a670d822ad3
- Size of remote file:
- 750 kB
- SHA256:
- 7902444b0b561c6a43b94959917e831133f28049e1ac79c3abd28899d8cf136c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.