Instructions to use procit011/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procit011/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="procit011/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("procit011/results") model = AutoModelForSequenceClassification.from_pretrained("procit011/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66d8dd1a9d5fca7f02a03bc1038d9fb4544d902ae60a74b15353925b46afd93a
- Size of remote file:
- 5.2 kB
- SHA256:
- 3bd2e1b317d72f921040deb7e1be4d92267cf308e39141bf9911c952260191aa
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