--- inference: false tags: - merge - mergekit - lazymergekit base_model: - senseable/Westlake-7B - Guilherme34/Samantha-v2 - uukuguy/speechless-mistral-six-in-one-7b license: apache-2.0 language: - en library_name: transformers pipeline_tag: conversational --- # Nandine-7b

Nandine

Nandine-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [senseable/Westlake-7B](https://huggingface.co/senseable/Westlake-7B) * [Guilherme34/Samantha-v2](https://huggingface.co/Guilherme34/Samantha-v2) * [uukuguy/speechless-mistral-six-in-one-7b](https://huggingface.co/uukuguy/speechless-mistral-six-in-one-7b) Nandine-7b represents a harmonious amalgamation of narrative skill, empathetic interaction, intellectual depth, and eloquent communication. **Key Features:** - **Narrative Excellence:** Drawing 55% of its prowess from Westlake-7B, Nandine-7b excels in crafting compelling narratives and engaging character dialogues. - **Diverse Expertise:** Benefits from the 35% contribution of speechless-mistral-six-in-one-7b, integrating insights from six advanced Mistral-7B models, covering areas like cognitive science, emotional intelligence, and social dynamics. - **Human Connection:** Gains a 10% influence from Samantha-v2, fostering a warm, approachable demeanor, enhancing user interaction quality while adhering to ethical guidelines. **Intended Use:** Ideal for users seeking a versatile AI companion for creative writing, thoughtful discussions, and general assistance. Nandine-7b aims to provide a delightful, insightful, and emotionally resonant user experience. **Limitations:** While Nandine-7b excels in various domains, it may not perfectly replicate human nuances in certain complex emotional or contextual scenarios. Users should be aware of these limitations in highly specialized or sensitive topics. ## 🧩 Configuration ```yaml models: - model: senseable/Westlake-7B parameters: weight: 0.55 density: 0.6 - model: Guilherme34/Samantha-v2 parameters: weight: 0.10 density: 0.3 - model: uukuguy/speechless-mistral-six-in-one-7b parameters: weight: 0.35 density: 0.6 merge_method: dare_ties base_model: mistralai/Mistral-7B-v0.1 parameters: int8_mask: true dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "sethuiyer/Nandine-7b" 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"]) ```