Instructions to use navendux/distilbert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use navendux/distilbert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="navendux/distilbert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("navendux/distilbert_model") model = AutoModelForSequenceClassification.from_pretrained("navendux/distilbert_model", device_map="auto") - 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 sha256:7efa9546605f02743fc0ca4a2b9bf1cb1e779e7aa894b2784eeaf4f1fd2ce887
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size 267832560
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