Sold by: NYSgpt
Deployed on AWS
Biomedical text embeddings for semantic search and RAG. Fine-tuned from bge-m3 on bioRxiv and medRxiv; outperforms NLM MedCPT on retrieval.
Overview
A dense retrieval encoder for biomedical text, fine-tuned from BAAI/bge-m3 on bioRxiv and medRxiv preprints. It maps queries, abstracts and passages to 1,024-dimension normalized embeddings for semantic search, retrieval-augmented generation and similarity analysis over life-sciences literature.
Performance
On a frozen, leakage-audited benchmark (MeSH concept queries searched against 433,449 preprints), it outperforms the US National Library of Medicine's MedCPT encoder: Recall@10 0.524 vs 0.457 (+15%, paired p = 1e-6), trained on roughly 2,500x less data. It also scores +83% over its base model and +49% over allenai/specter2_base on the same queries.
Input and output
Input: application/json {"inputs": ["text", ...]} or text/plain, one text per line. Output: {"embeddings": [[...1024 floats...]], "dimensions": 1024}.
Runs entirely in your account
CPU inference on ml.m5 and ml.c5 instances; no data leaves your AWS account. Model card: https://huggingface.co/NYSgpt/biomed-encoder
Highlights
- Outperforms NLM MedCPT on biomedical concept search (Recall@10 0.524 vs 0.457, +15%)
- 1,024-dimension normalized embeddings, JSON or plain-text input
- CPU inference; your data never leaves your AWS account
Details
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Dimensions summary
This listing is free to use, so you pay only for the AWS compute instances that run the model. You pick an instance type and an inference mode. Two instance types are offered: ml.m5.xlarge and ml.m5.2xlarge. A third type, ml.c5.2xlarge, is available for real-time only. Batch mode handles grouped jobs, while real-time mode serves live requests. All options bill per host hour (HostHrs), so cost scales with how long each instance runs. Larger or longer-running instances raise your hourly total.
Top-of-mind questions for buyers
Both modes bill per host hour. Real-time mode keeps an instance running to serve live requests, so you pay for all uptime. Batch mode runs on grouped jobs and bills only while the job processes. Batch suits scheduled embedding tasks; real-time suits live search queries.
One HostHrs is one hour of a single AWS machine learning instance running the encoder model. The instance type you pick — ml.m5.xlarge, ml.m5.2xlarge, or ml.c5.2xlarge — sets its CPU and memory. You are billed for each hour the instance stays active.
It is an embedding model fine-tuned on biomedical literature. It powers semantic search across health and pharmaceutical datasets, matching text by meaning rather than keywords. You run it on the instance type you choose, in either batch or real-time mode, and pay only for the compute hours used.
nysgpt.com
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Vendor refund policy
This product is free; there are no software charges to refund. AWS infrastructure charges are billed by AWS. Contact Brendan@nysgpt.com with any issue.
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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.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Initial release of the NYSgpt Biomedical Encoder.
Additional details
Inputs
- Summary
Biomedical text to embed: queries, abstracts or passages. JSON {"inputs": ["text", ...], "normalize": true} or text/plain with one text per line.
- Limitations for input type
- Inputs longer than 8,192 tokens are truncated.
- Input MIME type
- application/json, text/plain
{"inputs": ["CRISPR knockout screen identifies regulators of T cell exhaustion"]}
https://github.com/nyd-user-1/biomed-encoder-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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