Sentence Similarity
sentence-transformers
Safetensors
Transformers
bidirlm_omni
mteb
embedding
bidirectional
custom_code
Instructions to use BidirLM/BidirLM-Omni-2.5B-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BidirLM/BidirLM-Omni-2.5B-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BidirLM/BidirLM-Omni-2.5B-Embedding", 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] - Transformers
How to use BidirLM/BidirLM-Omni-2.5B-Embedding with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BidirLM/BidirLM-Omni-2.5B-Embedding", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
vllm compatibility
#1
by lxww301 - opened
Is there any plan for vllm compatibility?
Hey, nothing on our end for now. It might be best to check with the vllm community to see if they're interested 🤷♂️
Nicolas-BZRD changed discussion status to closed