Sentence Similarity
Transformers
Safetensors
bert
feature-extraction
cybersecurity
cti
yara
contrastive-learning
bi-encoder
text-embeddings-inference
Instructions to use shaswatamitra/falcon-yara-bi-e5-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shaswatamitra/falcon-yara-bi-e5-base-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("shaswatamitra/falcon-yara-bi-e5-base-v2") model = AutoModel.from_pretrained("shaswatamitra/falcon-yara-bi-e5-base-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "config": { | |
| "run": 2, | |
| "batch": 70, | |
| "epochs": 30, | |
| "lr": 2e-05, | |
| "schedule": "constant", | |
| "temperature": 0.05 | |
| }, | |
| "train_loss": [ | |
| 0.1847048169844562, | |
| 0.015805520707120498, | |
| 0.013420168024909106, | |
| 0.00935349129971915, | |
| 0.008315871799519906 | |
| ], | |
| "val_loss": [ | |
| 0.010712273850307005, | |
| 0.011096823183531038, | |
| 0.011594576649410252, | |
| 0.012432693288095228, | |
| 0.01301232461651125 | |
| ], | |
| "best_epoch": 1, | |
| "best_val_loss": 0.010712273850307005 | |
| } |