metadata
inference: false
base_model:
- SanjiWatsuki/Silicon-Maid-7B
- sethuiyer/Aika-7B
- sethuiyer/Nandine-7b
- mlabonne/AlphaMonarch-7B
library_name: transformers
tags:
- mergekit
- merge
- not-for-all-audiences
license: cc
model-index:
- name: sethuiyer/Diana-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: 68.34
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Diana-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: 86.73
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Diana-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: 64.58
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Diana-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: 60.55
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Diana-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: 80.19
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Diana-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: 63.23
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Diana-7B
name: Open LLM Leaderboard
language:
- en
pipeline_tag: conversational
Diana-7B
This is Diana-7b, rated 93.56/100 by GPT-4 on a collection of 30 synthetic prompts generated by GPT-4.
It is a merge of the following models using mergekit:
- mlabonne/AlphaMonarch-7B: This model has impressive conversational abilities, formal and sophisticated style, and strong reasoning skills.
- sethuiyer/Aika-7b: A merge of SanjiWatsuki/Silicon-Maid-7B, Guilherme34/Samantha-v2, jan-hq/stealth-v1.3, and senseable/WestLake-7B-v2, Aika-7b is designed for natural and human-like interactions, accurate information delivery, comprehensive analysis, emotional intelligence, clarity, and structure.
- SanjiWatsuki/Silicon-Maid-7B: This model is known for its excellent multi-turn conversational skills and logical coherence.
- sethuiyer/Nandine-7b: A merge of senseable/Westlake-7B, Guilherme34/Samantha-v2, and uukuguy/speechless-mistral-six-in-one-7b, Nandine-7b excels in narrative skill, empathetic interaction, intellectual depth, and eloquent communication.
By combining these models, Diana-7B offers a balanced blend of capabilities, making it suitable for various tasks and providing a comprehensive AI companion for creative writing, thoughtful discussions, problem-solving, and general assistance.
Configuration
The following YAML configuration was used to produce this model:
base_model: mlabonne/AlphaMonarch-7B
dtype: bfloat16
merge_method: dare_ties
models:
- model: mlabonne/AlphaMonarch-7B
- model: sethuiyer/Aika-7B
parameters:
density: 0.85
weight: 0.30
- model: SanjiWatsuki/Silicon-Maid-7B
parameters:
density: 0.85
weight: 0.50
- model: sethuiyer/Nandine-7b
parameters:
density: 0.85
weight: 0.30
parameters:
int8_mask: true
Prompt Template
{bos}user
{ .Prompt }{eos}
{bos}assistant
GGUF
GGUF files are available at Diana-7B-GGUF
Ollama
Diana is now available on Ollama. You can use it by running the command ollama run stuehieyr/diana
in your
terminal. If you have limited computing resources, check out this video to learn how to run it on
a Google Colab backend.