README.md

---
base_model:
- Jebadiah/Aria-coder-7b
tags:
- merge
- mergekit
- lazymergekit
- Jebadiah/Aria-coder-7b
---

# Aria-rp-coder-7b

Aria-rp-coder-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Jebadiah/Aria-coder-7b](https://huggingface.co/Jebadiah/Aria-coder-7b)

## 🧩 Configuration

```yaml
name: Jebadiah/Aria-tree-35-coder-7b
models:
  - model: Jebadiah/Aria-coder-7b
    parameters:
      density: 1.0
      weight: 1.0

merge_method: passthrough

layers:
  - source:
      layer_range: [0, 15]  # layers before the middle
    target:
      layer_range: [0, 15]

  - source:
      layer_range: [16, 16]  # duplicate layer 16
    target:
      layer_range: [16, 18]  # copy to positions 16, 17 and 18

  - source:
      layer_range: [17, 17]  # duplicate layer 17
    target:
      layer_range: [19, 20]  # copy to positions 19 and 20     

  - source:
      layer_range: [18, 31]  # layers after the middle (shifted by 3)
    target:
      layer_range: [21, 34]

dtype: float16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Jebadiah/Aria-rp-coder-7b"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```