README.md

---
license: apache-2.0
tags:
- moe
- merge
- mergekit
- lazymergekit
- phi3_mergekit
- microsoft/Phi-3-medium-128k-instruct
base_model:
- microsoft/Phi-3-medium-128k-instruct
- microsoft/Phi-3-medium-128k-instruct
---

# Phi3Mix

Phi3Mix is a Mixture of Experts (MoE) made with the following models using [Phi3_LazyMergekit](https://colab.research.google.com/drive/1Upb8JOAS3-K-iemblew34p9h1H6wtCeU?usp=sharing):
* [microsoft/Phi-3-medium-128k-instruct](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct)
* [microsoft/Phi-3-medium-128k-instruct](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct)


## 🧩 Configuration

```yaml
base_model: microsoft/Phi-3-medium-128k-instruct
gate_mode: cheap_embed
experts_per_token: 1
dtype: float16
experts:
  - source_model: microsoft/Phi-3-medium-128k-instruct
    positive_prompts: ["research, logic, math, science"]
  - source_model: microsoft/Phi-3-medium-128k-instruct
    positive_prompts: ["creative, art"]
```

## 💻 Usage

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model = "DarqueDante/Phi3Mix"

tokenizer = AutoTokenizer.from_pretrained(model)

model = AutoModelForCausalLM.from_pretrained(
    model,
    trust_remote_code=True,
)

prompt="How many continents are there?"
input = f"<|system|>You are a helpful AI assistant.<|end|><|user|>{prompt}<|assistant|>"
tokenized_input = tokenizer.encode(input, return_tensors="pt")

outputs = model.generate(tokenized_input, max_new_tokens=128, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(tokenizer.decode(outputs[0]))
```