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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmedjr/codebert-algorithm-tagger") model = AutoModelForSequenceClassification.from_pretrained("Ahmedjr/codebert-algorithm-tagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download requirements.txt from Ahmedjr/codebert-algorithm-tagger: direct link, hf CLI and curl.
- Browser
- Download file 34 Bytes
-
https://huggingface.co/Ahmedjr/codebert-algorithm-tagger/resolve/main/requirements.txt
- Command line
-
hf download hf://Ahmedjr/codebert-algorithm-tagger/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/Ahmedjr/codebert-algorithm-tagger/resolve/main/requirements.txt
34 Bytes
| transformers>=4.30.0 | |
| torch>=2.0.0 | |