Instructions to use BAAI/llm-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/llm-embedder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/llm-embedder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/llm-embedder") model = AutoModel.from_pretrained("BAAI/llm-embedder", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from BAAI/llm-embedder: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/BAAI/llm-embedder/resolve/refs%2Fpr%2F13/tokenizer.json
- Command line
-
hf download hf://BAAI/llm-embedder@refs/pr/13/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/BAAI/llm-embedder/resolve/refs%2Fpr%2F13/tokenizer.json
712 kB
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