Instructions to use shepherdgroup/NuTCRacker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shepherdgroup/NuTCRacker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="shepherdgroup/NuTCRacker")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("shepherdgroup/NuTCRacker") model = AutoModelForMaskedLM.from_pretrained("shepherdgroup/NuTCRacker") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:16fd596e4c3c1fb56ef2d081d68a6e61342594e501d54a4610775d306925514e
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size 238562892
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