Instructions to use research-dump/roberta_large_temp_classifier_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta_large_temp_classifier_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta_large_temp_classifier_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta_large_temp_classifier_v2") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta_large_temp_classifier_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f62997ed71af4d5871612ff380bf801aeadd053b2899f9b89256b254eed4db0
- Size of remote file:
- 1.42 GB
- SHA256:
- aa2a910a78c76e11e96324d1f36041bb593d114d9d3291fb73430cadc4efbc6b
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