Instructions to use research-dump/roberta_temp_classifier_bootstrapped with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta_temp_classifier_bootstrapped with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta_temp_classifier_bootstrapped")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta_temp_classifier_bootstrapped") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta_temp_classifier_bootstrapped", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6f446218b73d1e636aa498d61b9157aab425f7860624260b9d86e5edb1ea077
- Size of remote file:
- 499 MB
- SHA256:
- b1e5eafe168a61851ed69601aa9bbb94d621644c6ffae46e396cd8a77f43f6fb
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