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:
- f6582668008278db719570879d8fc1a7b5596ac5d3de5f304f361b41e11cfe08
- Size of remote file:
- 965 MB
- SHA256:
- abab3b4cf39c076b94517e5b7f53bf43a70e72032d787dde948c56a1c597df5d
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