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:
- 7071c888e2c7ab337311d477eec48fb1904dab7f3e026c3dd432f4a7a1bc42c5
- Size of remote file:
- 498 MB
- SHA256:
- 844dd955ffa92ae773150abb1be18d5e7614a0c4674ac909c2c2fecd0728d616
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.