Text Ranking
Transformers
Safetensors
Chinese
English
qwen3
text-generation
medical
code
math
reasoning
general
Instructions to use AQ-MedAI/Diver-Retriever-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AQ-MedAI/Diver-Retriever-4B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AQ-MedAI/Diver-Retriever-4B") model = AutoModelForCausalLM.from_pretrained("AQ-MedAI/Diver-Retriever-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from AQ-MedAI/Diver-Retriever-4B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/AQ-MedAI/Diver-Retriever-4B/resolve/main/tokenizer.json
- Command line
-
hf download hf://AQ-MedAI/Diver-Retriever-4B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AQ-MedAI/Diver-Retriever-4B/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- a7030cf2e58dead38199a68a8cd6f6f1a609a6072d7fb38ba5f85b3bb7e21557
- Size of remote file:
- 11.4 MB
- SHA256:
- 9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.