What is mental_health_counseling_conversations?

54/100
Trust Score (D)
⚠️ Use Caution

mental_health_counseling_conversations is a health that Amod/mental_health_counseling_conversations provides mental health counseling conversations.. It has a Nerq Trust Score of 54/100 (D). 465 GitHub stars. Published by Amod. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

54
TRUST SCORE
D
GRADE
465
STARS
1.7K
DOWNLOADS

What mental_health_counseling_conversations Does

mental_health_counseling_conversations is a dataset in the health category. Amod/mental_health_counseling_conversations provides mental health counseling conversations.. It is published by Amod and has no specified license. With 465 GitHub stars and 1.7K downloads, it has a growing community of users and contributors.

Who Should Use mental_health_counseling_conversations

mental_health_counseling_conversations is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.

Details

AuthorAmod
Categoryhealth
LicenseNot specified
Typedataset
SourceView on GitHub
Security Score0/100
Activity Score0/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=mental-health-counseling-conversations

Setup guide · Full safety report · Production review · Is it safe?

Safer Alternatives

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Frequently Asked Questions

What is mental_health_counseling_conversations used for?
mental_health_counseling_conversations is a health tool. Amod/mental_health_counseling_conversations provides mental health counseling conversations..
Is mental_health_counseling_conversations free?
License: Check project page. mental_health_counseling_conversations has 465 GitHub stars.
Is mental_health_counseling_conversations safe?
mental_health_counseling_conversations has a Nerq Trust Score of 54/100 (D). Use with caution.
What are alternatives to mental_health_counseling_conversations?
Top alternatives: MedicalGPT, open-health, Awesome-AI4Med. See full comparison.

Last updated September 2026. Trust scores based on automated analysis of public data.

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