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
Download config_sentence_transformers.json from geevec-ai/geevec-embeddings-1.0-lite: direct link, hf CLI and curl.
- Browser
- Download file 84 Bytes
-
https://huggingface.co/geevec-ai/geevec-embeddings-1.0-lite/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://geevec-ai/geevec-embeddings-1.0-lite/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/geevec-ai/geevec-embeddings-1.0-lite/resolve/main/config_sentence_transformers.json
84 Bytes
| { | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |