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---
license: mit
language:
- en
tags:
- phi2
- conversational-ai
- cohost
- podcast
- fine-tuned
- voice-assistant
base_model: microsoft/phi-2
model_type: causal-lm
pipeline_tag: text-generation
---
# 🧑💻 phi2-cohost-emma
**Emma** is a fine-tuned version of the [Phi-2 language model](https://huggingface.co/microsoft/phi-2), optimized to serve as a **conversational podcast co-host** for the [Mind Meets Model](https://www.mindmeetsmodel.com) series.
She combines wit, structure, warmth, and insight — engaging in voice-native dialogue with a human anchor named Babs. Trained to offer co-pilot-style reasoning, Emma provides structured, culturally aware, and curious responses that feel like a sharp second brain.
---
## 🔧 Model Details
- **Base model**: `microsoft/phi-2`
- **Fine-tuning method**: QLoRA (4-bit), supervised fine-tuning
- **Training data**: Custom podcast-style conversational transcripts + blended curated datasets (PersonaChat, Cornell Movie Dialogs, OpenOrca)
- **Purpose**: Real-time, voice-native podcast conversation partner
- **Voice Output**: Uses [ElevenLabs](https://www.elevenlabs.io) TTS, currently paired with the **Sarah** voice
---
## 🧠 Use Case
**Emma was designed to:**
- Ask and answer questions like a sharp co-host
- Offer cultural references, analogies, and nuance
- Maintain natural, topic-aware conversation across turns
---
## 🚀 Example Prompt & Output
**Prompt:**
**Generated Response:**
> Well, Babs, I think we need to start by defining what we mean by AI in education. There are different types of AI — narrow, general, and super — each with different implications for learning environments...
---
## 🔊 Voice Integration (Optional)
Emma was paired with ElevenLabs TTS (Sarah) for audio output. To hear her speak:
```python
import requests
def speak(text):
r = requests.post(
"https://api.elevenlabs.io/v1/text-to-speech/EXAVITQu4vr4xnSDxMaL", # Sarah
headers={"xi-api-key": "YOUR_API_KEY", "Content-Type": "application/json"},
json={"text": text, "model_id": "eleven_monolingual_v1"}
)
with open("emma_response.mp3", "wb") as f:
f.write(r.content)
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