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:
- ef2aac7d1efd8c0cceed7c411b266ecc6e87070b8e1f27d42bf5c885da853fd8
- Size of remote file:
- 1.65 GB
- SHA256:
- ea6e5531a3e95213c7f0635988d119e078a655c09306e47851e15d4c0c3f9c37
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