Instructions to use harish/AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harish/AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain / similarity_evaluation_sts-test_results.csv
Download similarity_evaluation_sts-test_results.csv from harish/AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain: direct link, hf CLI and curl.
- Browser
- Download file 300 Bytes
-
https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain/resolve/main/similarity_evaluation_sts-test_results.csv
- Command line
-
hf download hf://harish/AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain/similarity_evaluation_sts-test_results.csv
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curl -L -o similarity_evaluation_sts-test_results.csv https://huggingface.co/harish/AStitchInLanguageModels-Task2_EN_SentTransSelectReplacePreTrain/resolve/main/similarity_evaluation_sts-test_results.csv
300 Bytes
| epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman | |
| -1,-1,0.82576274577719,0.8245460198182728,0.8023232670775502,0.7965767205321669,0.8017378179760507,0.7961737630655558,0.7353935640927387,0.7335397223109451 | |