Instructions to use BAAI/BGE-VL-Screenshot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/BGE-VL-Screenshot with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/BGE-VL-Screenshot", 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
Download config_sentence_transformers.json from BAAI/BGE-VL-Screenshot: direct link, hf CLI and curl.
- Browser
- Download file 460 Bytes
-
https://huggingface.co/BAAI/BGE-VL-Screenshot/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://BAAI/BGE-VL-Screenshot/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/BAAI/BGE-VL-Screenshot/resolve/main/config_sentence_transformers.json
460 Bytes
| { | |
| "__version__": { | |
| "pytorch": "2.10.0+cu128", | |
| "sentence_transformers": "5.4.0", | |
| "transformers": "5.5.0" | |
| }, | |
| "default_prompt_name": "document", | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "document": "Represent the given text-rich image, focusing on extracting and interpreting both its rich text content and visual features.", | |
| "query": "Represent the given image with the given query." | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |