--- tags: - merge - mergekit - lazymergekit - Weyaxi/Einstein-v6-7B - argilla/CapybaraHermes-2.5-Mistral-7B base_model: - Weyaxi/Einstein-v6-7B - argilla/CapybaraHermes-2.5-Mistral-7B license: apache-2.0 --- # J.O.S.I.E.3-Beta12-7B-slerp J.O.S.I.E.3-Beta12-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Weyaxi/Einstein-v6-7B](https://huggingface.co/Weyaxi/Einstein-v6-7B) * [argilla/CapybaraHermes-2.5-Mistral-7B](https://huggingface.co/argilla/CapybaraHermes-2.5-Mistral-7B) This model has been further Finetuned on my custom J.O.S.I.E.v3.11 Dataset, in the ChatML prompt Format. ```text <|im_start|>system You are JOSIE, my private and superinteligent AI Assistant.<|im_end|> <|im_start|>user {{ .Prompt }}<|im_end|> <|im_start|>assistant {{ .Response }}<|im_end|> ``` ## 🧩 Configuration ```yaml slices: - sources: - model: Weyaxi/Einstein-v6-7B layer_range: [0, 32] - model: argilla/CapybaraHermes-2.5-Mistral-7B layer_range: [0, 32] merge_method: slerp base_model: argilla/CapybaraHermes-2.5-Mistral-7B 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 = "Isaak-Carter/J.O.S.I.E.3-Beta12-7B-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"]) ``` # Evaluation results: ```json { "all": { "acc": 0.635008846776534, 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