README.md

---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- rmdhirr/Foxglove_7B
- ResplendentAI/Paradigm_Shift_7B
- merge
- mergekit
- roleplay
- mistral
base_model:
- rmdhirr/Foxglove_7B
- ResplendentAI/Paradigm_Shift_7B
model-index:
- name: Anthesis_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: 69.03
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Anthesis_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: 86.2
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Anthesis_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: 62.06
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Anthesis_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: 68.65
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Anthesis_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: 78.93
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Anthesis_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: 42.99
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rmdhirr/Anthesis_7B
      name: Open LLM Leaderboard
---

# 🏵️ Anthesis_7B

Anthesis_7B is a merge of the following models:
* [rmdhirr/Foxglove_7B](https://huggingface.co/rmdhirr/Foxglove_7B)
* [ResplendentAI/Paradigm_Shift_7B](https://huggingface.co/ResplendentAI/Paradigm_Shift_7B)

# Formatting/Preset
Alpaca works best, but Mistral gives good outputs as well.

# Configuration
```yaml
models:
  - model: ResplendentAI/Paradigm_Shift_7B
    # no parameters necessary for base model
  - model: rmdhirr/Foxglove_7B
    parameters:
      density: 0.60
      weight: 0.40
merge_method: dare_ties
base_model: ResplendentAI/Paradigm_Shift_7B
parameters:
  int8_mask: true
dtype: bfloat16
```
# [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_rmdhirr__Anthesis_7B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |67.97|
|AI2 Reasoning Challenge (25-Shot)|69.03|
|HellaSwag (10-Shot)              |86.20|
|MMLU (5-Shot)                    |62.06|
|TruthfulQA (0-shot)              |68.65|
|Winogrande (5-shot)              |78.93|
|GSM8k (5-shot)                   |42.99|