Instructions to use dennlinger/roberta-cls-consec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dennlinger/roberta-cls-consec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dennlinger/roberta-cls-consec")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dennlinger/roberta-cls-consec") model = AutoModelForSequenceClassification.from_pretrained("dennlinger/roberta-cls-consec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61286787db0d8f6794afcfe64e45aa1785f951aaf6e81f86982e07a5347312ed
- Size of remote file:
- 501 MB
- SHA256:
- d255c70a5a7a531172f4a2be56f77a043e02348bfd35c9a915831bdc8de8c59c
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