---
language: en
tags:
- phi-2
- openassistant
- conversational
license: mit
---

# Phi-2 Fine-tuned on OpenAssistant

This model is a fine-tuned version of Microsoft's Phi-2 model, trained on the OpenAssistant dataset using QLoRA techniques.

## Model Description

- **Base Model:** Microsoft Phi-2
- **Training Data:** OpenAssistant Conversations Dataset
- **Training Method:** QLoRA (Quantized Low-Rank Adaptation)
- **Use Case:** Conversational AI and text generation

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("your-username/phi2-finetuned-openassistant")
tokenizer = AutoTokenizer.from_pretrained("your-username/phi2-finetuned-openassistant")

# Generate text
input_text = "Hello, how are you?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```

## Training Details

- Fine-tuned for 1 epoch
- Used 4-bit quantization for efficient training
- Implemented gradient checkpointing and mixed precision training

## Limitations

- The model inherits limitations from both Phi-2 and the OpenAssistant dataset
- May produce incorrect or biased information
- Should be used with appropriate content filtering and moderation

## License

This model is released under the MIT License.