--- base_model: - Yuma42/Llama3.1-SuperHawk-8B - nbeerbower/llama3.1-gutenberg-8B tags: - merge - mergekit - lazymergekit - Yuma42/Llama3.1-SuperHawk-8B - nbeerbower/llama3.1-gutenberg-8B license: llama3.1 --- # Llama3.1-IgneousIguana-8B Llama3.1-IgneousIguana-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Yuma42/Llama3.1-SuperHawk-8B](https://huggingface.co/Yuma42/Llama3.1-SuperHawk-8B) * [nbeerbower/llama3.1-gutenberg-8B](https://huggingface.co/nbeerbower/llama3.1-gutenberg-8B) ## 🧩 Configuration ```yaml slices: - sources: - model: Yuma42/Llama3.1-SuperHawk-8B layer_range: [0, 32] - model: nbeerbower/llama3.1-gutenberg-8B layer_range: [0, 32] merge_method: slerp base_model: Yuma42/Llama3.1-SuperHawk-8B parameters: t: - value: 0.2 dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "Yuma42/Llama3.1-IgneousIguana-8B" 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"]) ```