Text Classification
sentence-transformers
Safetensors
Transformers
multilingual
gemma
text-generation
Instructions to use BAAI/bge-reranker-v2-gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/bge-reranker-v2-gemma with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/bge-reranker-v2-gemma") 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-reranker-v2-gemma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BAAI/bge-reranker-v2-gemma")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-reranker-v2-gemma") model = AutoModelForCausalLM.from_pretrained("BAAI/bge-reranker-v2-gemma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
(404 Not Found) for url (https://huggingface.co/BAAI/bge-reranker-v2-gemma/resolve/main/pytorch_model.bin)
#4
by qwerasdfzxv - opened
To reproduce:
docker run -p 8080:80 ghcr.io/huggingface/text-embeddings-inference:cpu-1.2 --model-id=BAAI/bge-reranker-v2-gemma
The model is saved in safetensors format, so there is no pytorch_model.bin
Thanks for the reply.
Switching to ghcr.io/huggingface/text-embeddings-inference:cpu-latest solves it. Looks like they just added the support for model.safetensors.index.json in https://github.com/huggingface/text-embeddings-inference/commit/7c9b7cb251858b84bbcb7d4abc476ffa2c42b0d9