transformers safetensors mistral text-generation merge mergekit lazymergekit en base_model:Guilherme34/Samantha-v2 base_model:merge:Guilherme34/Samantha-v2 base_model:senseable/Westlake-7B base_model:merge:senseable/Westlake-7B base_model:uukuguy/speechless-mistral-six-in-one-7b base_model:merge:uukuguy/speechless-mistral-six-in-one-7b license:apache-2.0 model-index autotrain_compatible text-generation-inference region:us
---
base_model:
- senseable/Westlake-7B
- Guilherme34/Samantha-v2
- uukuguy/speechless-mistral-six-in-one-7b
language:
- en
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- merge
- mergekit
- lazymergekit
inference: false
model-index:
- name: sethuiyer/Nandine-7b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 69.28
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Nandine-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 87.01
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Nandine-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.83
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Nandine-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 62.1
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Nandine-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 83.19
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Nandine-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 62.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Nandine-7b
      name: Open LLM Leaderboard
---

# Nandine-7b

<p align="center">
  <img src="https://huggingface.co/sethuiyer/Nandine-7b/resolve/main/nandine.webp" height="128px" alt="Nandine">
</p>

This is Nandine-7b, rated **87.47/100** by GPT-4 on a collection of 30 synthetic prompts generated by GPT-4.

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.

## OpenLLM Benchmark

| Model                          | Average ⬆️ | ARC    | HellaSwag | MMLU  | TruthfulQA | Winogrande | GSM8K | 
|--------------------------------|------------|-------|-----------|-------|------------|------------|-------| 
| sethuiyer/Nandine-7b 📑       | 71.47      | 69.28 | 87.01     | 64.83 | 62.1       | 83.19      | 62.4  | 


## Nous Benchmark
|                          Model                          |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
|---------------------------------------------------------|------:|------:|---------:|-------:|------:|
|[Nandine-7b](https://huggingface.co/sethuiyer/Nandine-7b)|  43.54|  76.41|     61.73|   45.27|  56.74|

For more details, refer [here](https://huggingface.co/sethuiyer/Nandine-7b/blob/main/EVAL.md)


**Pros:**
1. **Strong Narrative Skills:** Excels in storytelling, creating engaging and imaginative narratives.
2. **Accurate Information Delivery:** Provides factual and detailed information across various topics.
3. **Comprehensive Analysis:** Capable of well-rounded discussions on complex and ethical topics.
4. **Emotional Intelligence:** Shows empathy and understanding in responses requiring emotional sensitivity.
5. **Clarity and Structure:** Maintains clear and well-structured communication.

**Cons:**
1. **Language Translation Limitations:** Challenges in providing fluent and natural translations.
2. **Incomplete Problem Solving:** Some logical or mathematical problems are not solved accurately.
3. **Lack of Depth in Certain Areas:** Needs deeper exploration in some responses for a more comprehensive understanding.
4. **Occasional Imbalance in Historical Context:** Some historical explanations could be more balanced.
5. **Room for Enhanced Creativity:** While creative storytelling is strong, there's potential for more varied responses in hypothetical scenarios.

**Intended Use:**
Ideal for users seeking a versatile AI companion for creative writing, thoughtful discussions, and general assistance.

## 🧩 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"])
```

## GGUF
GGUF files are available at [Nandine-7b-GGUF](https://huggingface.co/sethuiyer/Nandine-7b-GGUF/tree/main)

## Ollama
Nandine is now available on Ollama. You can use it by running the command ```ollama run stuehieyr/nandine``` in your 
terminal. If you have limited computing resources, check out this [video](https://www.youtube.com/watch?v=Qa1h7ygwQq8) to learn how to run it on 
a Google Colab backend.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_sethuiyer__Nandine-7b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |71.47|
|AI2 Reasoning Challenge (25-Shot)|69.28|
|HellaSwag (10-Shot)              |87.01|
|MMLU (5-Shot)                    |64.83|
|TruthfulQA (0-shot)              |62.10|
|Winogrande (5-shot)              |83.19|
|GSM8k (5-shot)                   |62.40|

