Instructions to use Falconsai/offensive_speech_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/offensive_speech_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Falconsai/offensive_speech_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Falconsai/offensive_speech_detection") model = AutoModelForSequenceClassification.from_pretrained("Falconsai/offensive_speech_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f233336684583ba96aaf66d29c55032895651dfc654090283fd1b81d371ef72
- Size of remote file:
- 3.96 kB
- SHA256:
- 4bcf015d7727fb95e74ccfb6fa4e500e13026ea93036073872f21f1c39aab86c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.