Sentence Similarity
Transformers
Safetensors
cybersecurity
cti
yara
contrastive-learning
dual-encoder
Instructions to use shaswatamitra/falcon-yara-dual-all-mpnet-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shaswatamitra/falcon-yara-dual-all-mpnet-base-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shaswatamitra/falcon-yara-dual-all-mpnet-base-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "config": { | |
| "run": 1, | |
| "batch": 50, | |
| "epochs": 10, | |
| "lr": 2e-05, | |
| "schedule": "constant", | |
| "temperature": 0.05 | |
| }, | |
| "train_loss": [ | |
| 0.025070763376739656, | |
| 0.007334003449147064, | |
| 0.008986924425698817, | |
| 0.0051783593970302156, | |
| 0.00574444390410979 | |
| ], | |
| "val_loss": [ | |
| 0.010351780250055205, | |
| 0.012851285916707745, | |
| 0.01365797114543538, | |
| 0.013854379174357319, | |
| 0.013845214853277225 | |
| ], | |
| "best_epoch": 1, | |
| "best_val_loss": 0.010351780250055205 | |
| } |