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:
- 828d0ef75e270ab2aeb2358cba3a69db8b24ab9c479fe2847c89b36163f76aa9
- Size of remote file:
- 16.6 MB
- SHA256:
- a2799ccc696b752ba00c34f58726bfe253a04921ceb6cfc620400f560474790b
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