Instructions to use HuggingFaceFW/fineweb-edu-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceFW/fineweb-edu-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceFW/fineweb-edu-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceFW/fineweb-edu-classifier") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceFW/fineweb-edu-classifier") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3ee955f153ce0d6a5322142798f539f4bc23cc966271e9922849ce56fed246e
- Size of remote file:
- 5.05 kB
- SHA256:
- efc02ff3cbe38771032be7435dde1ef98e3d99cdd38f1fb9a9c2f710ef949f0b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.