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google/gemma-4-12B-it with QLoRA on a blend of
mental-health counseling, empathetic-dialogue, and crisis-response datasets, merged, and exported to
GGUF Q4_K_M for low-latency, fully-local inference via llama.cpp (Ollama or llama-cpp-python).The REFRAME app layers CBT-style Socratic questioning (via its system prompt) on top of this mental-health-tuned base. It is a supportive conversationalist — not a clinician. See Limitations.
google/gemma-4-12B-it (12B)r=16, α=16, dropout=0, context 2048q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_projgemma4_mentalhealthbuddy_v1 (Ollama) · llama.cpp engineunsloth, peft, trl, bitsandbytes, accelerate, torch 2.10| Dataset | Hugging Face | Source / GitHub |
|---|---|---|
| MentalChat16K | ShenLab/MentalChat16K | PennShenLab/MentalChat16K · arXiv:2503.13509 |
| Mental Health Counseling Conversations | Amod/mental_health_counseling_conversations | sourced from counselchat.com |
| CounselChat | nbertagnolli/counsel-chat | nbertagnolli/counsel-chat |
| EmpatheticDialogues (LLM-formatted) | Estwld/empathetic_dialogues_llm | facebookresearch/EmpatheticDialogues |
| Mental-Health Crisis Responses (score-filtered) | arnaiztech/llms-mental-health-crisis-responses | ellisalicante/LLMs-Mental-Health-Crisis · arXiv:2509.24857 |
ollama run gemma4_mentalhealthbuddy_v11from llama_cpp import Llama
2llm = Llama.from_pretrained(
3 repo_id="emailvenky/gemma4-mentalhealthbuddy-v1",
4 filename="*Q4_K_M.gguf",
5 n_ctx=4096,
6)
7print(llm.create_chat_completion(messages=[{"role": "user", "content": "Hello"}]))