Instructions to use Tritkoman/EnglishtoChurchSlavonicV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tritkoman/EnglishtoChurchSlavonicV1 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="Tritkoman/EnglishtoChurchSlavonicV1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tritkoman/EnglishtoChurchSlavonicV1") model = AutoModelForSeq2SeqLM.from_pretrained("Tritkoman/EnglishtoChurchSlavonicV1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d92d431aa2b43aa82be667fec6aa347c491a998f44b28f4cee643914f636063
- Size of remote file:
- 4.92 GB
- SHA256:
- 21ac15bd0bf8d9027147616508c86cb04e16c3d8975fca22f9692ac832c94cc8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.