Instructions to use GleghornLab/AT_EXP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleghornLab/AT_EXP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GleghornLab/AT_EXP")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GleghornLab/AT_EXP") model = AutoModelForMaskedLM.from_pretrained("GleghornLab/AT_EXP") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 980da61958687111c95f8e5c44530e8d3ca5a586b0f4f954935e973b2cff6907
- Size of remote file:
- 62.2 MB
- SHA256:
- 4231d4ffe1bbb52fd83e00523939e6d3596c4660227fbc630b80fb3cc34a21e2
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