Feature Extraction
sentence-transformers
Safetensors
Transformers
gemma2
sentence-similarity
mteb
Eval Results (legacy)
Instructions to use BAAI/bge-multilingual-gemma2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/bge-multilingual-gemma2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/bge-multilingual-gemma2") 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 BAAI/bge-multilingual-gemma2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/bge-multilingual-gemma2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-multilingual-gemma2") model = AutoModel.from_pretrained("BAAI/bge-multilingual-gemma2") - Inference
- Notebooks
- Google Colab
- Kaggle
FlagEmbedding调用显卡问题
#4
by labniz - opened
os.environ["CUDA_VISIBLE_DEVICES"] = "[5,6]"? 还是 os.environ["CUDA_VISIBLE_DEVICES"] = "5,6"?呀
作者您好,不太清楚通过FlagEmbedding使用gpu的方式,输出会显示说
----------using 8*GPUs----------
但看显卡情况是没有用到
labniz changed discussion status to closed
labniz changed discussion status to open
labniz changed discussion title from os.environ["CUDA_VISIBLE_DEVICES"] to os.environ["CUDA_VISIBLE_DEVICES"]调用显卡问题
labniz changed discussion title from os.environ["CUDA_VISIBLE_DEVICES"]调用显卡问题 to FlagEmbedding调用显卡问题
是os.environ["CUDA_VISIBLE_DEVICES"] = "5,6"