Instructions to use jusgowiturs/Tamil_Bert_L3_Cube_Relative_Position with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jusgowiturs/Tamil_Bert_L3_Cube_Relative_Position with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jusgowiturs/Tamil_Bert_L3_Cube_Relative_Position")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jusgowiturs/Tamil_Bert_L3_Cube_Relative_Position") model = AutoModelForSequenceClassification.from_pretrained("jusgowiturs/Tamil_Bert_L3_Cube_Relative_Position") - Notebooks
- Google Colab
- Kaggle
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#1
by jusgowiturs - opened
eval_loss = 1.8664062388308413
mcc = 0.18692210989460428
MODEL_Archi = BERT
jusgowiturs changed pull request status to merged
Tamil BERT with relative position in attention mechanism