Feature Extraction
sentence-transformers
Safetensors
Transformers
qwen3_pseudo_moe
sentence-similarity
custom_code
Instructions to use geevec-ai/geevec-embeddings-1.0-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use geevec-ai/geevec-embeddings-1.0-lite with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("geevec-ai/geevec-embeddings-1.0-lite", 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 geevec-ai/geevec-embeddings-1.0-lite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="geevec-ai/geevec-embeddings-1.0-lite", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("geevec-ai/geevec-embeddings-1.0-lite", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update pseudo_moe_st_module.py
#3
by ctranslate2-4you - opened
Accept domain="general" in the Sentence Transformers module
model.encode(texts, domain="general") raises ValueError: Invalid domain: general, because the check only allows config.domain_names (coding, reasoning), even though the README documents general as the default route. This accepts "general" and includes it in the error message. Tested with sentence-transformers 6.1.0: "general" matches the default output, coding and reasoning are unchanged, and invalid domains still raise.
This has been superseded by https://huggingface.co/geevec-ai/geevec-embeddings-1.0-lite/discussions/4
ctranslate2-4you changed pull request status to closed