Instructions to use michaelfeil/ct2fast-nllb-200-3.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelfeil/ct2fast-nllb-200-3.3B 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="michaelfeil/ct2fast-nllb-200-3.3B")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("michaelfeil/ct2fast-nllb-200-3.3B") model = AutoModelForMultimodalLM.from_pretrained("michaelfeil/ct2fast-nllb-200-3.3B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 262dcf1b8263a8e72d2b585da25151da07ff58a3f77f7286a2623a4fd22b2cf6
- Size of remote file:
- 3.36 GB
- SHA256:
- 68b12b2b461a4ca0c3dee725d1d36b47f7ba8604810fce93e4a9fdacd2a4c33b
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