Sentence Similarity
sentence-transformers
Safetensors
English
llava_next
multimodal-retrieval
embedding-model
custom_code
Instructions to use BAAI/BGE-VL-MLLM-S1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/BGE-VL-MLLM-S1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/BGE-VL-MLLM-S1", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
LlavaNextProcessor from_pretrained Fails - tokenizer.json Loading Error
#2
by CrystalTang - opened
Exception at: model.set_processor("BAAI/BGE-VL-MLLM-S1")
When trying to load the BGE-VL-MLLM-S1 model, I encountered a tokenizer.json parsing error, even though the file was correctly downloaded. I also tried setting use_fast=False, but the issue persists.(my environment: transformers==4.44.2, Python 3.9.18, torch+CUDA: 2.0.1+cu117)