Feature Extraction
Transformers
Safetensors
sentence-transformers
Vietnamese
bgem3_projection
sentence-similarity
embeddings
vietnamese
rental
real-estate
custom_code
Instructions to use lamdx4/bge-m3-vietnamese-rental-projection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lamdx4/bge-m3-vietnamese-rental-projection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lamdx4/bge-m3-vietnamese-rental-projection", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lamdx4/bge-m3-vietnamese-rental-projection", trust_remote_code=True, dtype="auto") - sentence-transformers
How to use lamdx4/bge-m3-vietnamese-rental-projection with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lamdx4/bge-m3-vietnamese-rental-projection", trust_remote_code=True) 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
| { | |
| "model_type": "bgem3_projection", | |
| "base_model": "BAAI/bge-m3", | |
| "d_in": 1024, | |
| "d_out": 128, | |
| "use_layernorm": false, | |
| "freeze_encoder": true, | |
| "max_length": 512, | |
| "architectures": [ | |
| "BGEM3ProjectionModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "modeling_bgem3_projection.BGEM3ProjectionConfig", | |
| "AutoModel": "modeling_bgem3_projection.BGEM3ProjectionModel" | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.36.0" | |
| } |