Text Classification
Transformers
Safetensors
English
roberta
code
algorithms
competitive-programming
multi-label-classification
codebert
text-embeddings-inference
Instructions to use Ahmedjr/codebert-algorithm-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmedjr/codebert-algorithm-tagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmedjr/codebert-algorithm-tagger")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmedjr/codebert-algorithm-tagger") model = AutoModelForSequenceClassification.from_pretrained("Ahmedjr/codebert-algorithm-tagger") - Notebooks
- Google Colab
- Kaggle
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## Model Description
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This model predicts algorithmic tags/categories for competitive programming problems based on their problem descriptions and solution code.
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**Supported Tags:**
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- math
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## Model Description
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This model predicts algorithmic tags/categories for competitive programming problems based on their problem descriptions and solution code.
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**Supported Tags:**
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- math
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