Instructions to use Tanhim/translation-En2De with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanhim/translation-En2De 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="Tanhim/translation-En2De")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tanhim/translation-En2De") model = AutoModelForSeq2SeqLM.from_pretrained("Tanhim/translation-En2De", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Tanhim/translation-En2De: direct link, hf CLI and curl.
- Browser
- Download file 591 MB
-
https://huggingface.co/Tanhim/translation-En2De/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://Tanhim/translation-En2De@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Tanhim/translation-En2De/resolve/refs%2Fpr%2F1/optimizer.pt
591 MB
- Xet hash:
- 0fd91567dc7825152f7e1e0df5dc0ca1c036fe639154d7eefabd68b6acafcfcc
- Size of remote file:
- 591 MB
- SHA256:
- ede6643607c72cfe883ca1cfdea31d6a7b9210b637e78113ccb5c1894f818f4b
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