Instructions to use WindyTranslate/translate-umb-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-umb-en 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-umb-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-umb-en") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-umb-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-umb-en, with attribution and change statement
cc172b8 verified - Xet hash:
- ac5e7c3136af7af1ce2dc33d6bff2ddf30e0e5f5fa7618a6726311b7f808bd8c
- Size of remote file:
- 799 kB
- SHA256:
- 19612a2873c6e5b84f62bffc1468e78030b305d5435f6167905d38e73e642cd7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.