Sentence Similarity
sentence-transformers
OpenVINO
French
xlm-roberta
passage-retrieval
pruned
nncf
8-bit precision
text-embeddings-inference
Instructions to use DomosFS/french-bge-m3-openvino-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DomosFS/french-bge-m3-openvino-8bit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DomosFS/french-bge-m3-openvino-8bit") sentences = [ "C'est une personne heureuse", "C'est un chien heureux", "C'est une personne très heureuse", "Aujourd'hui est une journée ensoleillée" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
This model is a quantized version of DomosFS/french-bge-m3 and is converted to the OpenVINO format. This model was obtained via the nncf-quantization space with optimum-intel.
First make sure you have optimum-intel installed:
pip install optimum[openvino]
To load your model you can do as follows:
from optimum.intel import OVModelForFeatureExtraction
model_id = "DomosFS/french-bge-m3-openvino-8bit"
model = OVModelForFeatureExtraction.from_pretrained(model_id)
- Downloads last month
- 1