Instructions to use AutoDataBench/Retrieval-resources with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AutoDataBench/Retrieval-resources with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AutoDataBench/Retrieval-resources") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download models/Qwen3-4B-Instruct-2507/tokenizer.json from AutoDataBench/Retrieval-resources: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/AutoDataBench/Retrieval-resources/resolve/main/models/Qwen3-4B-Instruct-2507/tokenizer.json
- Command line
-
hf download hf://AutoDataBench/Retrieval-resources/models/Qwen3-4B-Instruct-2507/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AutoDataBench/Retrieval-resources/resolve/main/models/Qwen3-4B-Instruct-2507/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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