Instructions to use sadickam/vba-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sadickam/vba-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sadickam/vba-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sadickam/vba-distilbert") model = AutoModelForSequenceClassification.from_pretrained("sadickam/vba-distilbert") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#2)
Browse files- Adding `safetensors` variant of this model (b9663cd3be72c63fb0b3a780e4a744e12606f629)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c6c1a519441a8363874c11e83e6247e033804f3cf1392cada7adb8741fdc01e8
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size 267835644
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