--- tags: - merge - mergekit - lazymergekit - Kukedlc/Neural4gsm8k - Kukedlc/NeuralMaxime-7B-slerp base_model: - Kukedlc/Neural4gsm8k - Kukedlc/NeuralMaxime-7B-slerp --- # NeuralKrishna-7B-slerp NeuralKrishna-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Kukedlc/Neural4gsm8k](https://huggingface.co/Kukedlc/Neural4gsm8k) * [Kukedlc/NeuralMaxime-7B-slerp](https://huggingface.co/Kukedlc/NeuralMaxime-7B-slerp) ## 🧩 Configuration ```yaml slices: - sources: - model: Kukedlc/Neural4gsm8k layer_range: [0, 32] - model: Kukedlc/NeuralMaxime-7B-slerp layer_range: [0, 32] merge_method: slerp base_model: Kukedlc/NeuralMaxime-7B-slerp 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 = "Kukedlc/NeuralKrishna-7B-slerp" 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"]) ```