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OpenMed/OpenMed NER DNADetect SuperClinical 184M

Advanced NLP model for DNA detection and clinical text analysis

Status
Not yet determined
Last checked
Unverified
License
Open source
Pricing
Free tier · from $0
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What it is

This Hugging Face model specializes in named entity recognition (NER) for detecting DNA sequences within clinical texts, aiding in precision medicine and genomics research.

This model stands out with its specialized capability in detecting DNA sequences within clinical texts, making it uniquely suited for precision medicine and genomics research.

When it fits — and when it doesn’t

A good fit for

  • Research teams needing accurate DNA detection in clinical texts

  • Developers working on genomics applications requiring NER capabilities

  • Precision medicine initiatives focused on patient-specific genetic data

Look elsewhere if

  • Teams looking for general-purpose text analysis without specific focus on DNA sequences

  • Projects that require real-time processing of large volumes of clinical texts

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited generalizability beyond clinical texts

    Model is specifically trained for detecting DNA sequences in clinical texts and may not perform well on other types of text.

  2. 02

    Resource-intensive at inference time

    The model size (184M) requires significant memory and computational resources, which can slow down inference times especially in resource-constrained environments.

  3. 03

    Documentation lacks practical examples for integration

    Current documentation focuses more on theoretical aspects rather than providing clear, step-by-step instructions or code snippets for integrating the model into existing applications.

  4. 04

    Dependency on Hugging Face ecosystem

    The tool is tightly integrated with the Hugging Face platform, which could lead to vendor lock-in and potential issues if there are changes in the Hugging Face API or service availability.

  5. 05

    No support for non-Python environments

    The tool is primarily developed with Python in mind; while it can be accessed via REST APIs, there's no official support or SDKs for other programming languages like Java or C#.

What it does well

  • Specialized in DNA sequence detection within clinical texts

  • High accuracy for precision medicine applications

  • Open-source and freely available on Hugging Face

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up OpenMed/OpenMed NER DNADetect SuperClinical 184M

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →