README.md

---
base_model:
- deepseek-ai/deepseek-coder-6.7b-instruct
- m-a-p/OpenCodeInterpreter-DS-6.7B
tags:
- merge
- mergekit
- lazymergekit
- deepseek-ai/deepseek-coder-6.7b-instruct
- m-a-p/OpenCodeInterpreter-DS-6.7B
---

# deepseek-coder-ties

deepseek-coder-ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [deepseek-ai/deepseek-coder-6.7b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct)
* [m-a-p/OpenCodeInterpreter-DS-6.7B](https://huggingface.co/m-a-p/OpenCodeInterpreter-DS-6.7B)

## 🧩 Configuration

```yaml
models:
  - model: deepseek-ai/deepseek-coder-6.7b-instruct
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: m-a-p/OpenCodeInterpreter-DS-6.7B
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
merge_method: ties
base_model: deepseek-ai/deepseek-coder-6.7b-base
parameters:
  normalize: true
  int8_mask: true
dtype: float16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Zelknight463/deepseek-coder-ties"
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"])
```