AIencoder/Logic-Coder-7B

1---2base_model:3- Qwen/Qwen2.5-Coder-7B-Instruct4- Qwen/Qwen2.5-7B-Instruct5tags:6- merge7- mergekit8- lazymergekit9- Qwen/Qwen2.5-Coder-7B-Instruct10- Qwen/Qwen2.5-7B-Instruct11---12 13# Logic-Coder-7B14 15Logic-Coder-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):16* [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct)17* [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)18 19## 🧩 Configuration20 21```yaml22slices:23  - sources:24      - model: Qwen/Qwen2.5-Coder-7B-Instruct25        layer_range: [0, 28]26      - model: Qwen/Qwen2.5-7B-Instruct27        layer_range: [0, 28]28merge_method: slerp29base_model: Qwen/Qwen2.5-Coder-7B-Instruct30parameters:31  t:32    - filter: self_attn33      value: [0, 0.5, 0.3, 0.7, 1]34    - filter: mlp35      value: [1, 0.5, 0.7, 0.3, 0]36    - value: 0.537dtype: bfloat1638```39 40## 💻 Usage41 42```python43!pip install -qU transformers accelerate44 45from transformers import AutoTokenizer46import transformers47import torch48 49model = "AIencoder/Logic-Coder-7B"50messages = [{"role": "user", "content": "What is a large language model?"}]51 52tokenizer = AutoTokenizer.from_pretrained(model)53prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)54pipeline = transformers.pipeline(55    "text-generation",56    model=model,57    torch_dtype=torch.float16,58    device_map="auto",59)60 61outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)62print(outputs[0]["generated_text"])63```