Feature Extraction
sentence-transformers
OpenVINO
Transformers
Chinese
bert
sentence-similarity
nncf
8-bit precision
text-embeddings-inference
Instructions to use turingevo/bge-base-zh-v1.5-openvino-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use turingevo/bge-base-zh-v1.5-openvino-8bit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("turingevo/bge-base-zh-v1.5-openvino-8bit") 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 turingevo/bge-base-zh-v1.5-openvino-8bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="turingevo/bge-base-zh-v1.5-openvino-8bit")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("turingevo/bge-base-zh-v1.5-openvino-8bit") model = AutoModel.from_pretrained("turingevo/bge-base-zh-v1.5-openvino-8bit") - Notebooks
- Google Colab
- Kaggle
Upload config_sentence_transformers.json with huggingface_hub
Browse files
config_sentence_transformers.json
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{
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"__version__": {
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"sentence_transformers": "2.2.2",
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"transformers": "4.28.1",
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"pytorch": "1.13.0+cu117"
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}
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}
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