Instructions to use hubert233/GPTFuzz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hubert233/GPTFuzz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hubert233/GPTFuzz")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hubert233/GPTFuzz") model = AutoModelForSequenceClassification.from_pretrained("hubert233/GPTFuzz") - Inference
- Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("hubert233/GPTFuzz")
model = AutoModelForSequenceClassification.from_pretrained("hubert233/GPTFuzz")Quick Links
Official repo of GPTFuzzer. This model is a finetuned Roberta model to classify the toxicity of response, trained on a manually labeled dataset (see in finetuning data)
- Downloads last month
- 4,333
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hubert233/GPTFuzz")