Translation
Transformers
PyTorch
English
Chinese
m2m_100
text2text-generation
translate
text-translate
Instructions to use xnx3/translate100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xnx3/translate100 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="xnx3/translate100")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("xnx3/translate100") model = AutoModelForSeq2SeqLM.from_pretrained("xnx3/translate100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e82792bb621be399dd4f43b7747332ff934f0e7dd52bb54de005be071f1a46f5
- Size of remote file:
- 1.33 GB
- SHA256:
- 681bc87ca4e49c3cda5a853d1d530805e2bf4b340657d87fd4925d6622f063a6
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