Instructions to use research-dump/roberta_temp_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta_temp_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta_temp_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta_temp_classifier") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta_temp_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2dbdea3acc5bd2f6289b2afa1ad5636ac2d0adcde1ec384416e5b98fbfefe41
- Size of remote file:
- 499 MB
- SHA256:
- 5e0a534ef949cb38e587d890ee909b7eb3fb2694f70c0d52e9399649f0c12829
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