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
Commit History
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delete config file
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upload new model configuration file
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upload complete model text2sparql for Agricore
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upload new model file
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upload new T5 tokenizer configuration file
These are the files related to the new T5 tokenizer trained for the purposes of Agricored3b2341 -
Upload new T5 tokenizer config file
These are the files related to the new T5 tokenizer trained for the purposes of Agricore4849a7a -
upload special token map for new T5 tokenizer
These are the files related to the new T5 tokenizer trained for the purposes of Agricore94972e3 -
Delete special_tokens_map (3).json
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upload special tokens map
These are the files related to the new T5 tokenizer trained for the purposes of Agricore0ca3dc9 -
upload first draft of final AI model for Agricore
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Upload config.json
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initial commit
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