Instructions to use remotejob/gradientclassification_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use remotejob/gradientclassification_v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="remotejob/gradientclassification_v0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("remotejob/gradientclassification_v0") model = AutoModelForSequenceClassification.from_pretrained("remotejob/gradientclassification_v0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 123701ab084f0903b8c1273e50ffeda650c9d736425e32231557c20c842d9e0a
- Size of remote file:
- 498 MB
- SHA256:
- edbf7edcee68d4d23b9fb313c1d91393f4cc6a1fb8deb4b7646514ea636a1cfb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.