deepseek-coder-ties / README.md
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---
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"])
```