Instructions to use CenIA/nllb-200-3.3B-spa-rap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CenIA/nllb-200-3.3B-spa-rap 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="CenIA/nllb-200-3.3B-spa-rap")# Load model directly from transformers import AutoTokenizer, M2M100NLLB tokenizer = AutoTokenizer.from_pretrained("CenIA/nllb-200-3.3B-spa-rap") model = M2M100NLLB.from_pretrained("CenIA/nllb-200-3.3B-spa-rap") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2009cc55852d5ba2f54c07db4f1583b39683f5452e53f7b4b096c4ec42cf8f9
- Size of remote file:
- 6.69 GB
- SHA256:
- b3c68b2cd527fecb10ee7011025bb4719920599a7ed3ca76a3561f09eab06f5e
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