README.md

---
tags:
- merge
- mergekit
- lazymergekit
- microsoft/wavecoder-ultra-6.7b
base_model:
- microsoft/wavecoder-ultra-6.7b
- microsoft/wavecoder-ultra-6.7b
license: mit
pipeline_tag: text-generation
---

# CodeMaster v1 7b

CodeMaster v1 7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [microsoft/wavecoder-ultra-6.7b](https://huggingface.co/microsoft/wavecoder-ultra-6.7b)
* [microsoft/wavecoder-ultra-6.7b](https://huggingface.co/microsoft/wavecoder-ultra-6.7b)

## 🧩 Configuration

```yaml
slices:
- sources:
  - model: microsoft/wavecoder-ultra-6.7b
    layer_range:
    - 0
    - 32
  - model: microsoft/wavecoder-ultra-6.7b
    layer_range:
    - 0
    - 32
merge_method: slerp
base_model: microsoft/wavecoder-ultra-6.7b
parameters:
  t:
  - filter: self_attn
    value:
    - 0
    - 0.5
    - 0.3
    - 0.7
    - 1
  - filter: mlp
    value:
    - 1
    - 0.5
    - 0.7
    - 0.3
    - 0
  - value: 0.5
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "KingNish/CodeMaster-v1-7b"
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=8096, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```