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--- |
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license: mit |
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language: |
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- en |
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tags: |
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- phi2 |
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- conversational-ai |
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- cohost |
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- podcast |
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- fine-tuned |
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- voice-assistant |
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base_model: microsoft/phi-2 |
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model_type: causal-lm |
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pipeline_tag: text-generation |
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--- |
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# 🧑💻 phi2-cohost-emma |
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**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. |
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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. |
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--- |
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## 🔧 Model Details |
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- **Base model**: `microsoft/phi-2` |
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- **Fine-tuning method**: QLoRA (4-bit), supervised fine-tuning |
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- **Training data**: Custom podcast-style conversational transcripts + blended curated datasets (PersonaChat, Cornell Movie Dialogs, OpenOrca) |
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- **Purpose**: Real-time, voice-native podcast conversation partner |
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- **Voice Output**: Uses [ElevenLabs](https://www.elevenlabs.io) TTS, currently paired with the **Sarah** voice |
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--- |
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## 🧠 Use Case |
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**Emma was designed to:** |
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- Ask and answer questions like a sharp co-host |
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- Offer cultural references, analogies, and nuance |
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- Maintain natural, topic-aware conversation across turns |
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--- |
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## 🚀 Example Prompt & Output |
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**Prompt:** |
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**Generated Response:** |
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> 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... |
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--- |
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## 🔊 Voice Integration (Optional) |
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Emma was paired with ElevenLabs TTS (Sarah) for audio output. To hear her speak: |
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```python |
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import requests |
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def speak(text): |
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r = requests.post( |
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"https://api.elevenlabs.io/v1/text-to-speech/EXAVITQu4vr4xnSDxMaL", # Sarah |
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headers={"xi-api-key": "YOUR_API_KEY", "Content-Type": "application/json"}, |
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json={"text": text, "model_id": "eleven_monolingual_v1"} |
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) |
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with open("emma_response.mp3", "wb") as f: |
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f.write(r.content) |
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