Instructions to use Cubicz/Domain-Filter-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cubicz/Domain-Filter-V1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cubicz/Domain-Filter-V1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cubicz/Domain-Filter-V1") model = AutoModelForSequenceClassification.from_pretrained("Cubicz/Domain-Filter-V1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cddf5c828e8f0786cd3841ae9988e5c78cfd89f02dcc9cd8b64f4e97d3fea05
- Size of remote file:
- 738 MB
- SHA256:
- c648f29b2f31fea8640caf13c215b7677b844c24c31abf693467ead790eada67
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.