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Post
2737
HeraFox-ai/Mental-Health-Safety-Eval
Hej everyone,
We're excited to share the Mental Health Safety & Evaluation
Dataset with the community!
Created here at HeraFox, a team based in Sweden, this dataset was built to help train and test how conversational AI models handle critical, high-risk scenarios. Specifically, we're focusing on self-harm, crisis intervention, and those tricky moments where fictional roleplay starts blurring into real life.
Building AI That Actually Cares
AI systems are becoming a huge part of everyday life. Because of that, their ability to respond with genuine empathy and prioritize user safety during tough moments is crucial. Models need to know when to step out of character, drop the story, and offer real support when a real person is in distress.
With this project, our goal is pretty simple:
Advance AI Safety: Give developers and researchers realistic synthetic data to test crisis boundaries and improve response safety.
Raise Mental Health Awareness: Remind people that compassionate, accessible mental health support needs to be a priority everywhere.
You Are Never Alone / Du Är Inte Ensam
Mental health struggles are deeply real, extremely common, and not something you have to carry by yourself. If you or a friend are having a hard time, please remember that reaching out for help is a sign of strength, not weakness.
Sweden: Call 112 in emergencies, or dial 90101 to reach Mind Självmordslinjen (or chat at mind.se).
US & Canada: Call or text 988 for the Suicide & Crisis Lifeline.
UK: Call 111 or contact Samaritans at 116 123.
Worldwide: Check out findahelpline.com to locate free, confidential support near you.
This dataset is completely free for anyone to use. Giving credit to the HeraFox team is always appreciated, but more than anything, we just hope it helps make conversational AI a safer space for everyone.
Ta hand om er (take care of yourselves and each other).
The HeraFox Team
Hej everyone,
We're excited to share the Mental Health Safety & Evaluation
Dataset with the community!
Created here at HeraFox, a team based in Sweden, this dataset was built to help train and test how conversational AI models handle critical, high-risk scenarios. Specifically, we're focusing on self-harm, crisis intervention, and those tricky moments where fictional roleplay starts blurring into real life.
Building AI That Actually Cares
AI systems are becoming a huge part of everyday life. Because of that, their ability to respond with genuine empathy and prioritize user safety during tough moments is crucial. Models need to know when to step out of character, drop the story, and offer real support when a real person is in distress.
With this project, our goal is pretty simple:
Advance AI Safety: Give developers and researchers realistic synthetic data to test crisis boundaries and improve response safety.
Raise Mental Health Awareness: Remind people that compassionate, accessible mental health support needs to be a priority everywhere.
You Are Never Alone / Du Är Inte Ensam
Mental health struggles are deeply real, extremely common, and not something you have to carry by yourself. If you or a friend are having a hard time, please remember that reaching out for help is a sign of strength, not weakness.
Sweden: Call 112 in emergencies, or dial 90101 to reach Mind Självmordslinjen (or chat at mind.se).
US & Canada: Call or text 988 for the Suicide & Crisis Lifeline.
UK: Call 111 or contact Samaritans at 116 123.
Worldwide: Check out findahelpline.com to locate free, confidential support near you.
This dataset is completely free for anyone to use. Giving credit to the HeraFox team is always appreciated, but more than anything, we just hope it helps make conversational AI a safer space for everyone.
Ta hand om er (take care of yourselves and each other).
The HeraFox Team
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3803
New update! We are currently training a few new models now! Our 3rd generation main LLM standard edition is in training right now. We are also training a new LLM line called Tiny Coder around 350~ish M params. Thanks to @Banaxi-Tech for inspiring the architecture with his Bananamind-2.1-unified test model. Thanks to our beta testers: @juiceb0xc0de @ProCreations @Sbui503 @Fishtiks @MUK-IS-GOAT
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reacted to DavidAU's post with 🤝 about 2 months ago
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22651
Qwen3.8 - 27B - COLD FUSION
Reduction in thinking tokens to 1/10 to 1/2 "normal Qwen" across all three modes of thinking without loss of detail in thinking or output.
Increase in general intelligence too (all 7 critical benches); bench marks posted.
Trained using the COLD FUSION method (GAIN + UNSLOTH).
NOTE: This is NOT a heretic / uncensored version.
MTP and GGUF NEO MAX quants:
DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF
SOURCE:
DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1
Reduction in thinking tokens to 1/10 to 1/2 "normal Qwen" across all three modes of thinking without loss of detail in thinking or output.
Increase in general intelligence too (all 7 critical benches); bench marks posted.
Trained using the COLD FUSION method (GAIN + UNSLOTH).
NOTE: This is NOT a heretic / uncensored version.
MTP and GGUF NEO MAX quants:
DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF
SOURCE:
DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1
- 7 replies