Instructions to use research-dump/roberta_large_temp_classifier_bootstrapped_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_bootstrapped_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_bootstrapped_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta_large_temp_classifier_bootstrapped_v2") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta_large_temp_classifier_bootstrapped_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e965f1d500f007a33e7913265ef5fc9346ea93ee664bbc6ee8462dc36035b10a
- Size of remote file:
- 1.42 GB
- SHA256:
- 94a63d659f65bb8d67cbfc3fdb69c2b662c3abdae54edb8bbe198300528069db
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