Instructions to use WindyTranslate/translate-lt-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-lt-tr 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-lt-tr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-lt-tr") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-lt-tr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-lt-tr, with attribution and change statement
fe8aa51 verified Download source.spm from WindyTranslate/translate-lt-tr: direct link, hf CLI and curl.
- Browser
- Download file 832 kB
-
https://huggingface.co/WindyTranslate/translate-lt-tr/resolve/main/source.spm
- Command line
-
hf download hf://WindyTranslate/translate-lt-tr/source.spm
-
curl -L -o source.spm https://huggingface.co/WindyTranslate/translate-lt-tr/resolve/main/source.spm
832 kB
- Xet hash:
- 36bfe9c82640d52606019ea0a411ad65826d7f20a85bbf803a7a670f69f0aad1
- Size of remote file:
- 832 kB
- SHA256:
- 8e6b9a208668773dafdefdb3ef338388d22e2bc896bbabda258d79f1997c227e
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