winter-garden-7b-alpha/README.md

---
license: cc-by-nc-4.0
tags:
- merge
- conversational
- multi-task
pipeline_tag: text-generation
base_model:
- paulml/OmniBeagleSquaredMBX-v3-7B
- ZySec-AI/ZySec-7B-v1
- liminerity/Omningotex-7b-slerp
- localfultonextractor/Erosumika-7B
- KatyTheCutie/LemonadeRP-4.5.3
- cgato/Thespis-Krangled-7b
- CorticalStack/pastiche-crown-clown-7b-dare
- snorkelai/Snorkel-Mistral-PairRM-DPO
- MTSAIR/multi_verse_model
model-index:
- name: winter-garden-7b-alpha - "Smart Assistant"
  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: 65.19
      name: normalized accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/winter-garden-7b-alpha
      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: 85.36
      name: normalized accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/winter-garden-7b-alpha
      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: 65.2
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/winter-garden-7b-alpha
      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: 50.94
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/winter-garden-7b-alpha
      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: 80.35
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/winter-garden-7b-alpha
      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: 54.44
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/winter-garden-7b-alpha
      name: Open LLM Leaderboard
---

# Winter Garden 7B - α - "Smart Assistant"

It was mentioned that we are in the open ai dark winter; so I thought I would make myself a nice winter garden.

## An experiment

I've merged four partitions successfully in the past, so lets go for 9! I started with:

* Mistral-7B-v0.1

and merged in

* OmniBeagleSquaredMBX-v3-7B
* ZySec-7B-v1
* Omningotex-7b-slerp
* Erosumika-7B
* LemonadeRP-4.5.3
* Thespis-Krangled-7b
* pastiche-crown-clown-7b-dare
* Snorkel-Mistral-PairRM-DPO
* multi_verse_model
 
### 9-partition merge

All of the layers were partitioned in to 9 random bins.  Alternating models were slerped at [0...1], and [1...0] gradients; except attention, which was slerped at 0.03.

This means that the model is still predominantly ordered around base mistral - including half of the input and output layers, and 28% of attention.

### Other

Includes fast tokenizer.

## Chat Template

I put a conversational chat template, which takes "name", "to" (optional), and "content" as the turns.  It is designed to follow a transcript style chat which is used by some of the models.  This type of use-case is best done by outlining a scene and creating a character card.

```
### {% title %}
{% metadata %}

USER: Hello

ASSISTANT: Hi, how are you?

```

It leans to being a coder when given an `### Instruction`, follows `<s>[INST][/INST]`, and likes `<|user|>`, `<|assistant|>` as well.

A quite cheery and intelligent model.  Very good with science and math, but still capable of a decent amount of creativity for a 7b model.

## Scores

Metric | Score
---|---
Average | 66.91
ARC | 65.19
HellaSwag | 85.36
MMLU | 65.2
TruthfulQA | 50.94
Winogrande | 80.35
GSM8K | 54.44

[Details](https://huggingface.co/datasets/open-llm-leaderboard/details_maldv__winter-garden-7b-alpha)