Text Classification
Transformers
Safetensors
Portuguese
English
xlm-roberta
prompt-injection
portuguese
negative-results
data-leakage
text-embeddings-inference
Instructions to use RodrigoSFaria/ptbr-injection-e5large-v3pub with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RodrigoSFaria/ptbr-injection-e5large-v3pub with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RodrigoSFaria/ptbr-injection-e5large-v3pub")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RodrigoSFaria/ptbr-injection-e5large-v3pub") model = AutoModelForSequenceClassification.from_pretrained("RodrigoSFaria/ptbr-injection-e5large-v3pub", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Page level false alarms and windowing
#1
by guicybercode - opened
The 217 of 217 false alarms on PyPI READMEs: did you check whether the trigger is mostly imperative install instructions and code blocks, or does it also fire on plain prose sections? If it is mostly code blocks, stripping fenced code before scoring could be a cheap test to separate the two.