Instructions to use jbochi/madlad400-3b-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jbochi/madlad400-3b-mt 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="jbochi/madlad400-3b-mt")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jbochi/madlad400-3b-mt") model = AutoModelForSeq2SeqLM.from_pretrained("jbochi/madlad400-3b-mt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10928dbccb80a55cc63b1b70da6c7cee205141a8010a9c1fff7a91589d7e646e
- Size of remote file:
- 11.8 GB
- SHA256:
- 66ff5f8fcaf92291da486fdfbd4d5233cec90e1359348a56e3172c978b3a76d4
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