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
Download laya-classificador.json from RodrigoSFaria/ptbr-injection-e5large-v3pub: direct link, hf CLI and curl.
- Browser
- Download file 42 Bytes
-
https://huggingface.co/RodrigoSFaria/ptbr-injection-e5large-v3pub/resolve/main/laya-classificador.json
- Command line
-
hf download hf://RodrigoSFaria/ptbr-injection-e5large-v3pub/laya-classificador.json
-
curl -L -o laya-classificador.json https://huggingface.co/RodrigoSFaria/ptbr-injection-e5large-v3pub/resolve/main/laya-classificador.json
42 Bytes
| {"temperatura": 1.0, "prefixo": "query: "} |