Instructions to use harish/AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harish/AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain / similarity_evaluation_sts-test_results.csv
Download similarity_evaluation_sts-test_results.csv from harish/AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain: direct link, hf CLI and curl.
- Browser
- Download file 302 Bytes
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain/resolve/main/similarity_evaluation_sts-test_results.csv
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain/similarity_evaluation_sts-test_results.csv
-
curl -L -o similarity_evaluation_sts-test_results.csv https://huggingface.co/harish/AStitchInLanguageModels-Task2_PT_SentTransSelectReplacePreTrain/resolve/main/similarity_evaluation_sts-test_results.csv
302 Bytes
| epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman | |
| -1,-1,0.8035028522066161,0.7840632290313927,0.7926912629504568,0.7789003788517304,0.7931069304802928,0.7793550123481766,0.6810272322988469,0.6358724809628449 | |