Instructions to use harish/SemEval2022Task2SubTask2ABaseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/SemEval2022Task2SubTask2ABaseline with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harish/SemEval2022Task2SubTask2ABaseline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download similarity_evaluation_sts-test_results.csv from harish/SemEval2022Task2SubTask2ABaseline: direct link, hf CLI and curl.
- Browser
- Download file 301 Bytes
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https://huggingface.co/harish/SemEval2022Task2SubTask2ABaseline/resolve/main/similarity_evaluation_sts-test_results.csv
- Command line
-
hf download hf://harish/SemEval2022Task2SubTask2ABaseline/similarity_evaluation_sts-test_results.csv
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curl -L -o similarity_evaluation_sts-test_results.csv https://huggingface.co/harish/SemEval2022Task2SubTask2ABaseline/resolve/main/similarity_evaluation_sts-test_results.csv
301 Bytes
| epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman | |
| -1,-1,0.8292630828165106,0.7998076959816071,0.8111914537624083,0.7957289259772087,0.811263624860446,0.7959313320750702,0.7583753141076951,0.6920700766848666 | |