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README.md

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+---
+base_model:
+- Qwen/Qwen2.5-Coder-7B-Instruct
+- Qwen/Qwen2.5-7B-Instruct
+tags:
+- merge
+- mergekit
+- lazymergekit
+- Qwen/Qwen2.5-Coder-7B-Instruct
+- Qwen/Qwen2.5-7B-Instruct
+---
+
+# Logic-Coder-7B
+
+Logic-Coder-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct)
+* [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: Qwen/Qwen2.5-Coder-7B-Instruct
+    parameters:
+      density: 1.0
+      weight: 1.0
+  - model: Qwen/Qwen2.5-7B-Instruct
+    parameters:
+      density: 0.5
+      weight: 0.5
+merge_method: ties
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+parameters:
+  normalize: true
+  int8_mask: true
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "AIencoder/Logic-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"])
+```