Instructions to use joligmueller/MSBA_M4_T10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joligmueller/MSBA_M4_T10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joligmueller/MSBA_M4_T10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joligmueller/MSBA_M4_T10") model = AutoModelForSequenceClassification.from_pretrained("joligmueller/MSBA_M4_T10") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:6e3d01e0d775b00d507a0fc712b4c7ae74e6f6109f71637be1b91e3816b1b2bf
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size 437962832
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