Instructions to use LieUr/tensorized-bert-rte-archive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LieUr/tensorized-bert-rte-archive with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LieUr/tensorized-bert-rte-archive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| ca473cc204a0803ae9925196ca6b36ad0eeea89287c33f3a3e38b598833abcff bak/chkpt_not_onlylr.pt | |
| 4e83c3e62926e7369e2ac57468dc3d30ae47b3bde264754b6cdea63daa29146d bak/chkpt_onlylr.pt | |
| d59624f85a9a786c7469b917d601f48218037d3a02a26ab91683856edfc41698 checkpoints/cola_bert_llama_mlp_large_0.7-004/model.pt | |
| 8926736860cdad46ca4bf2ab1a6583abe6ba624e4a4d1cd99b72c3212762e119 checkpoints/cola_bert_llama_mlp_large_0.7_only_lr-001/model.pt | |
| 550826d2c11a257454dafa3eafd28c7466b2ff4e1596ac6a6e0e34b135224cac model_checkpoints/rte_cola_bert_llama_mlp_large_0.7_only_lr-001/2e2e91ae-step=68-val_accuracy=0.7329.ckpt | |
| 80e12db4425c32bbdbe40dbb54e3910b153a88043c27164c09ae352c444f76cb model_checkpoints/colaBert_rte_mlpId_0.7329_2e2e91ae/model.safetensors | |