--- tags: - merge - mergekit - lazymergekit - teknium/OpenHermes-2.5-Mistral-7B - mistralai/Mistral-7B-v0.1 base_model: - teknium/OpenHermes-2.5-Mistral-7B - mistralai/Mistral-7B-v0.1 --- # MistGem-7B-slerp MistGem-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) * [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) ## 🧩 Configuration ```yaml models: # - model: google/gemma-7b # # no parameters necessary for base model - model: teknium/OpenHermes-2.5-Mistral-7B parameters: density: 0.5 weight: 0.5 - model: mistralai/Mistral-7B-v0.1 parameters: density: 0.5 weight: 0.3 merge_method: ties base_model: mistralai/Mistral-7B-v0.1 parameters: normalize: true dtype: float16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "codegood/MistGem-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"]) ```