Instructions to use rmtariq/malay_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rmtariq/malay_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rmtariq/malay_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rmtariq/malay_classification") model = AutoModelForSequenceClassification.from_pretrained("rmtariq/malay_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbcffb662e720e02d9b5b9196c3e749b67fa8dfa8be740d6893484f490a79144
- Size of remote file:
- 5.78 kB
- SHA256:
- 7d4172e68b34bbb724cc06f92ca232f233dc0e6190390192bb1c35a633af40bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.