Translation
Transformers
PyTorch
TensorBoard
marian
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use shed-e/Translation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shed-e/Translation 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="shed-e/Translation")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shed-e/Translation") model = AutoModelForSeq2SeqLM.from_pretrained("shed-e/Translation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download target.spm from shed-e/Translation: direct link, hf CLI and curl.
- Browser
- Download file 802 kB
-
https://huggingface.co/shed-e/Translation/resolve/main/target.spm
- Command line
-
hf download hf://shed-e/Translation/target.spm
-
curl -L -o target.spm https://huggingface.co/shed-e/Translation/resolve/main/target.spm
802 kB
- Xet hash:
- 45b306e487e34ffcb94071ef015f0b97a9d0e89a28b77f46490a22d53f80928e
- Size of remote file:
- 802 kB
- SHA256:
- 78d0e717c77053f1c4b856d8661d9cb87c64f083a35418c087b9146300e4f585
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