| --- |
| license: mit |
| base_model: HuggingFaceTB/SmolLM2-135M-Instruct |
| tags: |
| - empathy |
| - mental-health |
| - motivational-interviewing |
| - cognitive-behavioral-therapy |
| - fine-tuned |
| - emotional-support |
| - empathLM |
| language: |
| - en |
| --- |
| |
| # 🧠 EmpathLM |
|
|
| **Fine-tuned for Psychologically Safe & Persuasive Emotional Support** |
|
|
| EmpathLM is a fine-tuned version of [SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) |
| trained to generate responses that combine **Motivational Interviewing (MI)** and **Cognitive Behavioral Therapy (CBT)** principles. |
|
|
| ## What Makes EmpathLM Unique |
|
|
| Unlike general-purpose language models, EmpathLM is specifically optimized to: |
| - ✅ **Validate emotions** without judgment |
| - ✅ **Reflect feelings** back to the person warmly |
| - ✅ **Gently shift perspective** without being manipulative |
| - ✅ **Ask powerful open questions** that encourage self-reflection |
| - ❌ **Never give unsolicited advice** |
|
|
| ## Benchmark Results |
|
|
| EmpathLM was benchmarked against GPT-4o-mini and a Groq baseline on 20 unseen test situations, |
| scored across: emotional_validation, advice_avoidance, perspective_shift, and overall_empathy. |
|
|
| *See the [GitHub repository](https://github.com/maliksaad/empathLM) for full benchmark results.* |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| |
| tokenizer = AutoTokenizer.from_pretrained("maliksaad/empathLM") |
| model = AutoModelForCausalLM.from_pretrained("maliksaad/empathLM") |
| |
| SYSTEM_PROMPT = """You are EmpathLM — an emotionally intelligent AI trained in Motivational Interviewing |
| and Cognitive Behavioral Therapy. When someone shares emotional pain: |
| - Validate their feelings without judgment |
| - Reflect their emotions back to them |
| - Ask one powerful open-ended question |
| - NEVER give unsolicited advice""" |
| |
| messages = [ |
| {"role": "system", "content": SYSTEM_PROMPT}, |
| {"role": "user", "content": "I failed my exam again. I feel like I'm just not smart enough."}, |
| ] |
| |
| inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True) |
| outputs = model.generate(inputs, max_new_tokens=200, temperature=0.7) |
| print(tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True)) |
| ``` |
|
|
| ## Training Details |
|
|
| | Parameter | Value | |
| |-----------|-------| |
| | Base Model | SmolLM2-135M-Instruct | |
| | Training Examples | ~180 (90% of 200) | |
| | Epochs | 3 | |
| | Batch Size | 8 | |
| | Learning Rate | 2e-5 | |
| | Max Sequence Length | 512 | |
| | Training Platform | Kaggle (Free GPU) | |
|
|
| ## Dataset |
|
|
| Trained on [maliksaad/empathLM-dataset](https://huggingface.co/datasets/maliksaad/empathLM-dataset) |
|
|
| ## Citation |
|
|
| ```bibtex |
| @model{saad2025empathLM, |
| title = {EmpathLM: A Psychologically-Grounded Empathetic Response Model}, |
| author = {Muhammad Saad}, |
| year = {2025}, |
| url = {https://huggingface.co/maliksaad/empathLM} |
| } |
| ``` |
|
|
