Instructions to use STAM/agricore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use STAM/agricore with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("STAM/agricore") model = AutoModelForSeq2SeqLM.from_pretrained("STAM/agricore", device_map="auto") - Notebooks
- Google Colab
- Kaggle
upload first draft of final AI model for Agricore
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:042b36644b0ab366271009e3bcffd1b30af5223244c21acddb98ba5d9103fee6
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size 68701522
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