---
language:
- en
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- linkedin
- content-generation
- text-generation
- gguf
- ollama
- llama-cpp
quantized_by: Manoghn
model_type: mistral
---

# VoiceCraft GGUF - Ollama Ready

Quantized GGUF versions of VoiceCraft fine-tuned on LinkedIn post generation.

## 🚀 Quick Start
```bash
# Download model
huggingface-cli download Manoghn/voicecraft-mistral-7b-gguf --local-dir ./voicecraft

# Quantize to smaller size (recommended)
cd voicecraft
llama.cpp/quantize voicecraft-f16.gguf voicecraft-q4_k_m.gguf q4_k_m

# Import to Ollama
ollama create voicecraft -f Modelfile

# Run
ollama run voicecraft "Generate a LinkedIn post about AI trends"
```

## 📦 Files

| File | Size | Description | Use Case |
|------|------|-------------|----------|
| `voicecraft-f16.gguf` | ~14GB | Full 16-bit precision | Highest quality, quantize locally |
| `Modelfile` | - | Ollama configuration | Pre-configured parameters |

**Recommended**: Download the f16 version and quantize to q4_k_m on your machine (~4GB).

## 🎯 Model Information

- **Base Model**: Mistral-7B-Instruct-v0.2
- **Fine-tuning**: Custom LinkedIn post dataset (380 examples)
- **Training**: 3 epochs, eval_loss: 0.7598
- **Specialization**: 4 LinkedIn post types

### Post Types

1. **AI Trend/News** - Technical and insightful
2. **Career Learning** - Reflective and growth-focused
3. **Project Update** - Achievement-focused with metrics
4. **Personal Insight** - Authentic and vulnerable

## 💻 Local Quantization

After downloading, quantize to your preferred size:
```bash
# 4-bit (smallest, recommended for most users)
llama.cpp/quantize voicecraft-f16.gguf voicecraft-q4_k_m.gguf q4_k_m

# 5-bit (balanced quality/size)
llama.cpp/quantize voicecraft-f16.gguf voicecraft-q5_k_m.gguf q5_k_m

# 8-bit (higher quality)
llama.cpp/quantize voicecraft-f16.gguf voicecraft-q8_0.gguf q8_0
```

## 🔧 Generation Parameters

Recommended settings (already in Modelfile):

- **temperature**: 0.8
- **top_p**: 0.95
- **repeat_penalty**: 1.15
- **num_predict**: 300

## 📚 Usage Example
```bash
ollama run voicecraft

>>> Post Type: Personal Insight
>>> Topic: Overcoming failure
>>> Style: Authentic and vulnerable
>>> Generate a LinkedIn post
```

## 🔗 Related

- **Original Model**: [Manoghn/voicecraft-mistral-7b](https://huggingface.co/Manoghn/voicecraft-mistral-7b)
- **Base Model**: [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)

## 📄 License

Apache 2.0 (inherited from Mistral-7B)

## 🙏 Acknowledgments

- Mistral AI for the base model
- Hugging Face for training infrastructure
- llama.cpp for GGUF conversion tools