Instructions to use aieng-lab/codebert-base_story-points with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aieng-lab/codebert-base_story-points with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aieng-lab/codebert-base_story-points")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/codebert-base_story-points") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/codebert-base_story-points", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b32996834e34f364a92aad6d5429f0fb5e127e9e0aac0cae1109ad44cb3e38f9
- Size of remote file:
- 249 MB
- SHA256:
- 1b9b5958875b3e295820642abfdda41110e94901b0220658e1f0b2f9e11280e5
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