Instructions to use jackxinning/Leanly_AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use jackxinning/Leanly_AI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="jackxinning/Leanly_AI", filename="Leanly_AI_14B_CHINESE_NONTHINK/Leanly_AI_14B_CHINESE_NONTHINK.gguf", )
llm.create_chat_completion( messages = "{\n \"question\": \"What is my name?\",\n \"context\": \"My name is Clara and I live in Berkeley.\"\n}" ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jackxinning/Leanly_AI with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf jackxinning/Leanly_AI # Run inference directly in the terminal: llama cli -hf jackxinning/Leanly_AI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jackxinning/Leanly_AI # Run inference directly in the terminal: llama cli -hf jackxinning/Leanly_AI
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf jackxinning/Leanly_AI # Run inference directly in the terminal: ./llama-cli -hf jackxinning/Leanly_AI
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf jackxinning/Leanly_AI # Run inference directly in the terminal: ./build/bin/llama-cli -hf jackxinning/Leanly_AI
Use Docker
docker model run hf.co/jackxinning/Leanly_AI
- LM Studio
- Jan
- Ollama
How to use jackxinning/Leanly_AI with Ollama:
ollama run hf.co/jackxinning/Leanly_AI
- Unsloth Studio
How to use jackxinning/Leanly_AI with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jackxinning/Leanly_AI to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jackxinning/Leanly_AI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jackxinning/Leanly_AI to start chatting
- Pi
How to use jackxinning/Leanly_AI with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jackxinning/Leanly_AI
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "jackxinning/Leanly_AI" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use jackxinning/Leanly_AI with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jackxinning/Leanly_AI
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default jackxinning/Leanly_AI
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use jackxinning/Leanly_AI with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jackxinning/Leanly_AI
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "jackxinning/Leanly_AI" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use jackxinning/Leanly_AI with Docker Model Runner:
docker model run hf.co/jackxinning/Leanly_AI
- Lemonade
How to use jackxinning/Leanly_AI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jackxinning/Leanly_AI
Run and chat with the model
lemonade run user.Leanly_AI-{{QUANT_TAG}}List all available models
lemonade list
- Leanly_AI
- Overview
- Clinical Focus
- From Generic Reassurance to Clinically Oriented Support
- Model Development
- Expected Output Structure
- Clinical Logic and Interpretability
- Weight-Stigma-Reducing Communication
- Local Deployment and Privacy
- Intended Uses
- Out-of-Scope Uses
- Relationship Between Leanly_AI and Leanly Agent
- Preliminary Evaluation
- Key Characteristics
- Important Safety Statement
- Core Summary
- Overview
Leanly_AI
Overview
Leanly_AI is a family of domain-adapted large language models developed by researchers from the Department of Endocrinology and Metabolism and the Department of General Practice at Provincial Hospital Affiliated to Fuzhou University.
The models are designed for psychological support and clinician–patient communication in obesity and clinical weight management settings. Leanly_AI aims to help physicians respond more consistently and empathetically to emotional difficulties that may arise during weight management, while maintaining medically cautious, structured, and clinically interpretable outputs.
Leanly_AI is the locally deployable text-model component of the broader Leanly Agent system. The text model generates supportive responses, practical behavioral suggestions, psychological risk reminders, and weight-management-related health information. The complete Leanly Agent workflow can additionally transform de-identified model outputs into physician reports, patient reports, health education materials, and illustrated educational tips.
For additional information and deployment guidance, please visit:
Clinical Focus
Weight management is often accompanied by emotional and behavioral challenges. Individuals with obesity may experience:
- Anxiety about treatment outcomes or weight regain
- Low mood and frustration during weight-loss plateaus
- Guilt or self-blame after dietary lapses
- Emotional eating or perceived loss of control
- Body image distress
- Weight-related stigma
- Reduced confidence and self-efficacy
- Treatment fatigue and reduced motivation
- Sleep-related or social difficulties affecting weight management
These problems do not always meet the diagnostic criteria for a mental disorder, but they may still affect eating behavior, physical activity, treatment adherence, follow-up attendance, and long-term engagement.
Leanly_AI is designed to support clinicians in addressing these common emotional difficulties through non-judgmental communication, practical guidance, and appropriate risk reminders.
From Generic Reassurance to Clinically Oriented Support
General conversational models may respond to emotional distress with broad encouragement such as:
“Do not be sad.” “Keep going.” “You can do it.”
Although well intentioned, such responses may not adequately address the complex emotional burden experienced during obesity treatment.
Leanly_AI is designed to provide more structured support by:
- Identifying the main emotional concern expressed by the user
- Acknowledging distress without judgment or blame
- Explaining possible relationships between emotions, eating behavior, sleep, physical activity, and treatment adherence
- Providing small and practical actions that can be implemented in daily life
- Avoiding stigmatizing, moralizing, or shame-inducing language
- Highlighting situations that may require further professional evaluation
- Reminding users that short-term weight fluctuations do not necessarily represent personal failure
The model is intended to support clinical communication rather than provide generic emotional companionship.
Model Development
Leanly_AI was developed by performing supervised fine-tuning on Qwen3 base models.
Base models
The current model family includes variants based on:
- Qwen3-4B
- Qwen3-14B
Both Chinese and English models were developed. Thinking and non-thinking variants are available, resulting in eight model configurations across language, parameter size, and reasoning mode.
Training dataset
The supervised fine-tuning dataset contains approximately 2,100 question–answer pairs focused on emotional support during obesity treatment and weight management.
The questions cover topics including:
- Anxiety and depressive emotions
- Emotional eating
- Weight-loss plateaus
- Fear of weight regain
- Body image concerns
- Social avoidance
- Sleep difficulties
- Self-blame and loss of confidence
- Reduced treatment motivation
- Difficulties maintaining dietary and physical activity plans
Approximately 53% of the questions were derived from de-identified questions raised by patients in clinical weight-management settings. The remaining questions were generated to broaden coverage of relevant emotional and behavioral scenarios.
The training answers were distilled from multiple teacher models and formatted according to a standardized clinical communication template. A subset of the generated answers was reviewed by mental health professionals.
Fine-tuning method
The models were trained using supervised fine-tuning with the LoRA parameter-efficient fine-tuning method through LLaMA-Factory.
The training objective was to improve the models’ ability to:
- Recognize emotional concerns relevant to weight management
- Provide supportive and non-stigmatizing responses
- Generate practical behavioral suggestions
- Summarize the main emotional issue
- Estimate the apparent severity of emotional distress based on the available text
- Provide appropriate reminders when professional psychological assessment may be needed
Expected Output Structure
Depending on the model variant and prompt template, Leanly_AI can generate:
- A supportive response addressing the user’s main concern
- A clinically oriented explanation of the emotional or behavioral problem
- Practical and achievable self-management suggestions
- Weight-management-related health education
- Six brief supportive tips
- A summary of the main emotional state
- An estimated level of emotional distress
- A short explanation supporting the estimated severity
- A recommendation for further assessment when high-risk information is explicitly present
Risk-related conclusions must be based only on information contained in the user’s input. The model should not fabricate or infer suicidal ideation, self-harm, purging, uncontrolled binge eating, medication misuse, or other high-risk behaviors when they have not been explicitly described.
Clinical Logic and Interpretability
Leanly_AI emphasizes clinically interpretable communication rather than unrestricted conversational generation.
Its response strategy focuses on:
- Emotional difficulties that may interfere with weight management
- Psychological distress associated with weight stigma
- Body image concerns and internalized weight bias
- Shame, guilt, and self-blame following perceived treatment failure
- Emotional eating and treatment-related frustration
- Situations that may require psychological or psychiatric assessment
- Communication strategies that reduce judgment and stigma
- Small, practical actions that may support continued engagement in treatment
The model is intended to help physicians understand the structure of supportive communication. A typical response follows a clinically understandable sequence:
Identify the concern → acknowledge the emotion → explain relevant mechanisms → provide practical actions → assess risk signals → recommend professional support when appropriate.
Weight-Stigma-Reducing Communication
A central design principle of Leanly_AI is the avoidance of weight-stigmatizing language.
The model is trained to avoid expressions that portray obesity as evidence of:
- Weak willpower
- Laziness
- Lack of discipline
- Moral failure
- Personal irresponsibility
Instead, obesity is treated as a complex chronic condition influenced by biological, behavioral, psychological, social, and environmental factors.
Leanly_AI encourages person-first, non-judgmental communication and aims to reduce shame-based interactions that may negatively affect trust, follow-up attendance, and treatment engagement.
Local Deployment and Privacy
Leanly_AI is designed for local deployment.
When deployed locally through tools such as Ollama and Open-WebUI:
- Patient input can remain on the local computer
- The text model can operate without an internet connection
- Original patient information does not need to be transmitted to an external model provider
- Institutions can maintain greater control over model access and data handling
The broader Leanly Agent system uses a hybrid architecture. Original patient input is first processed locally. Only content that has undergone privacy filtering and de-identification may be transferred to an online agent workflow for document generation or multimodal material production.
De-identification reduces privacy risk but does not guarantee absolute anonymity. Institutional information-security policies, access controls, audit procedures, and human review remain necessary.
Intended Uses
Leanly_AI may be used as an auxiliary tool for:
- Supporting clinician–patient communication in weight-management clinics
- Drafting non-judgmental responses to emotional concerns
- Providing low-intensity, non-therapeutic emotional support
- Generating practical behavioral suggestions
- Supporting weight-stigma-reducing communication
- Identifying text-based signals that may require further clinical assessment
- Preparing educational or communication materials for physician review
- Training clinicians in structured and empathetic communication
- Conducting research on domain-specific medical language models
All clinically relevant outputs should be reviewed by a qualified healthcare professional before being used in patient care.
Out-of-Scope Uses
Leanly_AI should not be used:
- To independently diagnose depression, anxiety disorders, eating disorders, or other psychiatric conditions
- To replace psychiatrists, psychologists, physicians, or other qualified professionals
- To provide psychotherapy or psychiatric treatment
- To make autonomous referral or emergency decisions
- To determine whether a patient is safe without professional assessment
- To prescribe, stop, or adjust medication
- To generate final medical records without clinician review
- As the sole basis for managing suicidal ideation, self-harm, severe hopelessness, purging, uncontrolled binge eating, or medication misuse
- As a substitute for emergency services or established clinical pathways
Individuals with acute self-harm or suicide risk, severe psychological distress, suspected eating disorders, or other urgent safety concerns require immediate assessment by qualified healthcare professionals.
Relationship Between Leanly_AI and Leanly Agent
The two terms refer to different components:
Leanly_AI
Leanly_AI is the locally deployable text-model family. It processes patient descriptions and generates supportive, structured, and clinically oriented text.
Leanly Agent
Leanly Agent is the complete clinical-support workflow built around Leanly_AI. After privacy filtering and de-identification, the system can use predefined agent skills to generate:
- A structured physician report
- A patient-friendly support report
- Psychological risk reminders
- Follow-up and communication suggestions
- Six brief health education tips
- Illustrated educational materials
Therefore, downloading Leanly_AI provides access to the text model, but not necessarily all document-generation and multimodal functions of the complete Leanly Agent workflow.
Preliminary Evaluation
In the preliminary evaluation reported by the development team, domain fine-tuning improved the performance of the local Qwen3-4B and Qwen3-14B models on weight-management-related emotional-support tasks compared with their corresponding base models.
The thinking variants achieved higher median evaluation scores than the non-thinking variants and approached the performance of some larger online models on this specific task.
These findings should be interpreted cautiously because:
- The evaluation focused on a specific clinical communication task
- Part of the evaluation relied on an automated judge model
- The study was conducted by the development team
- Independent external validation has not yet been completed
- Text-quality performance does not establish clinical effectiveness
- The model has not been demonstrated to replace professional psychological assessment
The current evidence supports preliminary feasibility and task-specific usefulness rather than definitive clinical efficacy.
Key Characteristics
✅ Developed specifically for obesity and weight-management settings ✅ Supports Chinese and English ✅ Includes 4B and 14B model sizes ✅ Includes thinking and non-thinking variants ✅ Supports local and offline deployment ✅ Uses non-judgmental and stigma-reducing communication ✅ Generates structured and clinically interpretable responses ✅ Provides practical, low-intensity emotional support suggestions ✅ Includes reminders for potential psychological risk ✅ Designed for physician-assisted use ✅ Does not replace psychological or psychiatric professionals
Important Safety Statement
Leanly_AI is a research and clinical communication support model.
It is not a medical device, an autonomous diagnostic system, or a substitute for professional care. Its output may be incomplete, inaccurate, overly general, or unsuitable for a particular individual.
All patient-facing materials, risk classifications, referral suggestions, and clinical reports generated with Leanly_AI or Leanly Agent must be reviewed and approved by a qualified healthcare professional.
Core Summary
Leanly_AI is a locally deployable, clinically oriented language-model family designed to support emotional communication during obesity treatment and weight management. It combines medical knowledge, real-world clinical scenarios, non-stigmatizing communication principles, and structured risk reminders to assist physicians in providing more consistent, empathetic, and practical support.
Leanly_AI — Supporting more comprehensive, respectful, and sustainable weight-management care.
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