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
Encountered an error while running the example.
#1
by i2vec - opened
Is the processor_config.json missing from the weight ?
same
That's because when processing the image,the patch_size is None,I solve this by manual set the patch_size in anaconda3/envs/your_envs_name/lib/python3.10/site-packages/transformers/models/llava_next/processing_llava_next.py line 84.
I don't know what the patch_size should be,so I set the same patch_size as the one in config.json which is 14.
After doing this the model runs well temporarily.
Hope BAAI authority can fix this soon.
