Instructions to use research-dump/roberta-base_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-base_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-base_temp_classifier_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta-base_temp_classifier_v2") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta-base_temp_classifier_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 793e06f2a75f433df797e8711e299068e3d8918c3bd6b37fd7f6eb64d27a550d
- Size of remote file:
- 499 MB
- SHA256:
- 7a0f72ea691af502997b6bb44cfc414bf48ac5bff05277a013e119a0e7e75acd
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