Instructions to use procit011/fine_tuned_robbert2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procit011/fine_tuned_robbert2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="procit011/fine_tuned_robbert2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("procit011/fine_tuned_robbert2") model = AutoModelForSequenceClassification.from_pretrained("procit011/fine_tuned_robbert2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2e5e33c9abb177cf73dfc5fcc15a3f9f706ab723067fe80e5372a46b37daa81
- Size of remote file:
- 467 MB
- SHA256:
- 849b9aa270e9345fcbcb137f43933599942c916153dc00f62cc48632965f3477
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