Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
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distilbert
text-embeddings-inference
Instructions to use fmops/distilbert-prompt-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fmops/distilbert-prompt-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fmops/distilbert-prompt-injection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fmops/distilbert-prompt-injection") model = AutoModelForSequenceClassification.from_pretrained("fmops/distilbert-prompt-injection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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 sha256:2e4646e1f03c0ced285c67a52353b829ff6d76a1bf35ab5ee0beb19dd4447eef
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size 267832560
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