inner-space-1b-sft-cbt

build-small-hackathon/inner-space-1b-sft-cbt

inner-space-1b-sft-cbt is a text generation model from build-small-hackathon. Use it when you need the model to write or continue text. It is set up for peft.

InnerSpace CBT Reflection LoRA is a QLoRA adapter for openbmb/MiniCPM5-1B-SFT. It is trained for the InnerSpace Hugging Face Space, a private journaling and reflection app that turns a journal entry into a structured…

Downloads · 30 days

4% of all-time downloads

All-time downloads

368

Public

Repo size

53.9 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.json9.9 MB · 54%

At a glance

Task: Text Generation
Library: peft
Access: Public
Created: Jun 6, 2026
Updated: Jun 8, 2026
SHA: 6720533c

Try a prompt

Base models

openbmb/MiniCPM5-1B-SFT

Spaces

build-small-hackathon/innerspace

Model card

From the Hugging Face model README

InnerSpace CBT Reflection LoRA

InnerSpace CBT Reflection LoRA is a QLoRA adapter for openbmb/MiniCPM5-1B-SFT. It is trained for the InnerSpace Hugging Face Space, a private journaling and reflection app that turns a journal entry into a structured CBT-informed reflection.

This adapter is not a clinical model. It does not provide diagnosis, treatment, medical advice, crisis counseling, or a replacement for licensed care.

Intended Use

Structured reflective journaling
Gentle CBT-informed self-reflection
Identifying emotions, affected life areas, and common cognitive distortions
Producing a balanced reframe, tiny next step, and reflective question
Brief follow-up coaching when the user responds with self-critical thoughts

Output Format

For journal analysis, the adapter is trained to produce exactly six sections:

=== EMOTIONS ===
=== LIFE AREAS ===
=== COGNITIVE DISTORTIONS ===
=== BALANCED REFRAME ===
=== TINY NEXT STEP ===
=== REFLECTION ===

For follow-up chat, the adapter is trained to stay brief, avoid hidden reasoning tags, avoid business-style skill metrics, validate the feeling, separate feeling from evidence, and ask one grounded question.

Training Recipe

Base model: openbmb/MiniCPM5-1B-SFT
Method: QLoRA with 4-bit NF4 quantization
Adapter: rank 16 LoRA on attention projections
Hardware: Modal NVIDIA A10G
Training set: 30 structured journal examples and 15 multi-turn coach examples
Sequence length: 1536 tokens
App runtime: Hugging Face Space with local model execution only

Safety Notes

The model should respond with supportive reflection, not certainty. It should not diagnose the user, prescribe treatment, provide crisis intervention, or claim to know whether the user's thoughts are objectively true. For immediate danger or crisis situations, users should contact local emergency services or a crisis hotline.