Sold by: NYSgpt
Deployed on AWS
A 22.7M-parameter reranker for scientific papers. Beats OpenAI embeddings at top-1 accuracy (87% vs 68%) at a fraction of the size and cost.
Overview
A compact cross-encoder reranker for scientific literature, fine-tuned from cross-encoder/ms-marco-MiniLM-L-6-v2 on peer-review-to-paper pairs. Built for latency-bound search where every millisecond counts.
Beats OpenAI embeddings at a fraction of the size
On a held-out benchmark of 3,157 queries over 1,534 scientific papers, it picks the correct paper first 87% of the time vs 68% for OpenAI's general embeddings (+19 points), with MRR 91.4% vs 74.5%. It also beats hybrid retrieval (87% vs 73%), at 22.7M parameters and about 7 ms per query. Benchmark: https://huggingface.co/datasets/NYSgpt/44b-eval
Input and output
Input: JSON {"query": "text", "documents": ["text", ...]}. Output: relevance scores and a ranking, highest first.
Runs entirely in your account
CPU inference on ml.m5 and ml.c5 instances. Model card: https://huggingface.co/NYSgpt/44b-reranker-mini
Highlights
- Beats OpenAI embeddings: 87% vs 68% top-1 accuracy at ranking scientific papers
- 22.7M parameters, about 7 ms per query: fast and cheap to run
- CPU inference; your data never leaves your AWS account
Details
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $1.50 |
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $1.50 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $1.50 |
ml.m5.2xlarge Inference (Real-Time) | Model inference on the ml.m5.2xlarge instance type, real-time mode | $1.50 |
ml.c5.2xlarge Inference (Real-Time) | Model inference on the ml.c5.2xlarge instance type, real-time mode | $1.50 |
Vendor refund policy
Software fees are billed hourly while your endpoint or batch job runs; stop the endpoint to stop charges. Contact Brendan@nysgpt.com about billing issues within 30 days.
Legal
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
Initial release.
Additional details
Inputs
- Summary
A query and a list of candidate documents: JSON {"query": "text", "documents": ["text", ...], "top_k": 10}, or {"pairs": [["query", "document"], ...]}.
- Limitations for input type
- Queries and documents are trimmed to the lengths used in training.
- Input MIME type
- application/json
{"query": "CRISPR screens in T cells", "documents": ["A CRISPR knockout screen identifies regulators of T cell exhaustion", "Wastewater surveillance of SARS-CoV-2 variants"]}
https://github.com/nyd-user-1/nysgpt-rerankers-sagemaker/blob/main/data/sample-input.json
Support
Vendor support
Support by email from the publisher (Brendan@nysgpt.com ); typical response within one business day. Usage notebook:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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