Feature Extraction
Transformers
Safetensors
English
bert
information-retrieval
mteb
scientific-retrieval
text-embeddings-inference
Instructions to use thu-nmrc/bge-small-structural-separator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thu-nmrc/bge-small-structural-separator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="thu-nmrc/bge-small-structural-separator")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("thu-nmrc/bge-small-structural-separator") model = AutoModel.from_pretrained("thu-nmrc/bge-small-structural-separator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from thu-nmrc/bge-small-structural-separator: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/thu-nmrc/bge-small-structural-separator/resolve/main/tokenizer.json
- Command line
-
hf download hf://thu-nmrc/bge-small-structural-separator/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/thu-nmrc/bge-small-structural-separator/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.