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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 229 Bytes
04a5f96 | 1 2 3 4 5 6 | 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
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