Sentence Similarity
sentence-transformers
Safetensors
Transformers
Chinese
English
qwen2
feature-extraction
bnb-my-repo
text-embeddings-inference
4-bit precision
bitsandbytes
Instructions to use wolframko/bge-code-v1-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use wolframko/bge-code-v1-bnb-4bit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("wolframko/bge-code-v1-bnb-4bit") sentences = [ "那是 個快樂的人", "那是 條快樂的狗", "那是 個非常幸福的人", "今天是晴天" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use wolframko/bge-code-v1-bnb-4bit with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("wolframko/bge-code-v1-bnb-4bit") model = AutoModel.from_pretrained("wolframko/bge-code-v1-bnb-4bit") - Notebooks
- Google Colab
- Kaggle
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