--- license: other license_name: helpingai license_link: https://helpingai.co/license pipeline_tag: text-generation language: - en tags: - HelpingAI - SER - Emotional Reasoning - Conversational AI library_name: transformers ---
❀️ HAI-SER
GitHub Organization Hugging Face Model License Join Community Discussion
[πŸ“œ License](https://helpingai.co/license) | [🌐 Website](https://helpingai.co)
Model Type Task Version
## 🌟 About HAI-SER **HAI-SER** is HelpingAI's revolutionary **Structured Emotional Reasoning (SER) model**, crafted to redefine the emotional intelligence of AI. Unlike traditional models, **HAI-SER goes beyond words**β€”it understands emotions, breaks down mental states, and offers **real, empathetic insights** for human-AI interaction. πŸš€ ### πŸ’‘ Core Features of HAI-SER The **Structured Emotional Reasoning (SER) framework** is built upon these key pillars: - **Emotional Vibe Check** – Reads emotional energy from conversations 🎭 - **Mind-State Analysis** – Understands thoughts, moods, and mental shifts 🧠 - **Root Cause Deep-Dive** – Identifies why emotions arise πŸ” - **Impact Check** – Evaluates how emotions affect real-life actions πŸ’₯ - **Safety Check** – Prioritizes user well-being 🚨 - **Healing Game Plan** – Offers structured support for growth & recovery πŸ’ͺ - **Growth Potential** – Helps users evolve emotionally πŸ“ˆ - **How to Approach** – Guides users in communication & self-awareness 🀝 ## πŸš€ Implementation ### Load HAI-SER with Hugging Face Transformers ```python from transformers import AutoModelForCausalLM, AutoTokenizer # Load HAI-SER model = AutoModelForCausalLM.from_pretrained("HelpingAI/HAI-SER") tokenizer = AutoTokenizer.from_pretrained("HelpingAI/HAI-SER") # Example usage chat = [ {"role": "system", "content": "You are an emotionally intelligent AI assistant who always thinks step by step before responding."}, {"role": "user", "content": "I feel really stressed out about my exams."} ] inputs = tokenizer.apply_chat_template( chat, add_generation_prompt=True, return_tensors="pt" ) outputs = model.generate( inputs, max_new_tokens=128, temperature=0.7, top_p=0.9, ) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) ``` ## βš™οΈ Training Details ### πŸ‹οΈ Training Data * Trained on a curated dataset emphasizing emotional intelligence, human psychology, and nuanced conversation. * Includes dialogues from mental health scenarios, coaching sessions, and empathetic responses. ### πŸ“Œ Capabilities * **Understands and analyzes emotions** with high accuracy. * **Provides tailored emotional insights** instead of generic responses. * **Capable of deep reasoning** for emotional problem-solving. ## ⚠️ Limitations * **Still evolving** – may not always capture deep emotions perfectly. * **Not a replacement for professional therapy** – designed to support, not diagnose. * **Best used with human moderation** in sensitive situations. ## πŸ“š Citation ```bibtex @misc{haiser2025, author = {HelpingAI Team}, title = {HAI-SER: Structured Emotional Reasoning for Empathetic AI}, year = {2025}, publisher = {HelpingAI}, journal = {HuggingFace}, howpublished = {\url{https://huggingface.co/HelpingAI/HAI-SER}} } ``` --- **Created with ❀️ by HelpingAI** [🌐 Website](https://helpingai.co) β€’ [πŸ“œ License](https://helpingai.co/license) β€’ [πŸ€— HuggingFace](https://huggingface.co/HelpingAI) β€’ [πŸ’¬ Discord](https://discord.gg/YweJwNqrnH)