Feature Extraction
sentence-transformers
ONNX
English
bert
web-agent
bi-encoder
element-selection
mind2web
text-embeddings-inference
Instructions to use doeve/web-agent-bge-small-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use doeve/web-agent-bge-small-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("doeve/web-agent-bge-small-v1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "format_version": "v1", | |
| "training_phase": 1, | |
| "trained_on": "2026-04-29", | |
| "base_model": "BAAI/bge-small-en-v1.5", | |
| "training_data_size": 5825, | |
| "training_data_source": "mind2web", | |
| "metrics_summary": { | |
| "top1_acc": 0.8042, | |
| "vs_baseline_delta": 0.1379, | |
| "baseline": "BAAI/bge-small-en-v1.5" | |
| }, | |
| "tokenizer_max_length": 256, | |
| "embedding_dim": 384, | |
| "use_mean_pooling": true | |
| } |