Instructions to use claritylab/MARS-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use claritylab/MARS-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="claritylab/MARS-Encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("claritylab/MARS-Encoder") model = AutoModelForSequenceClassification.from_pretrained("claritylab/MARS-Encoder") - Notebooks
- Google Colab
- Kaggle
| epoch,steps,Pearson_Correlation,Spearman_Correlation | |
| 0,-1,0.7995245439207993,0.6101085726851492 | |
| 1,-1,0.818848196591943,0.6125101699388535 | |
| 2,-1,0.8218412832248984,0.6127352398765499 | |
| 3,-1,0.8060285162981113,0.6111382204076435 | |