Instructions to use WindyTranslate/translate-tr-eo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-tr-eo 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-tr-eo")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-tr-eo") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-tr-eo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-tr-eo, with attribution and change statement
2bfde17 verified - Xet hash:
- e0f6a2c31be28a1e40a8fb6a9f983ad7d031b7afb0ac0b5d5594ff5fb53f3100
- Size of remote file:
- 303 kB
- SHA256:
- 8701547ce83eef26e37de2462c7ff6257b22b52c74205481e63a5472114296ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.