README.md

---
language:
- en
license: cc-by-sa-4.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- liminerity/Multiverse-Experiment-slerp-7b
- jeiku/Alpaca_NSFW_Shuffled_Mistral
- ResplendentAI/Datura_7B
- ChaoticNeutrals/Eris_Remix_7B
datasets:
- ResplendentAI/Alpaca_NSFW_Shuffled
- unalignment/toxic-dpo-v0.2
model-index:
- name: Paradigm_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: 73.63
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Paradigm_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: 88.66
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Paradigm_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: 64.02
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Paradigm_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: 75.19
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Paradigm_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: 84.53
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Paradigm_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: 66.79
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Paradigm_7B
      name: Open LLM Leaderboard
---
# Paradigm

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/626dfb8786671a29c715f8a9/euhpckYXwNiNiq-Lh4Fi-.jpeg)

GGUF available here: https://huggingface.co/Lewdiculous/Paradigm_7B-GGUF-IQ-Imatrix

### Configuration

The following YAML configuration was used to produce this model:

```yaml
merge_method: dare_ties
base_model: ChaoticNeutrals/Eris_Remix_7B
parameters:
  normalize: true
models:
  - model: ChaoticNeutrals/Eris_Remix_7B
    parameters:
      weight: 1
  - model: ResplendentAI/Datura_7B
    parameters:
      weight: 1
  - model: liminerity/Multiverse-Experiment-slerp-7b+jeiku/Alpaca_NSFW_Shuffled_Mistral
    parameters:
      weight: 0.33
dtype: float16
```
# [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_ResplendentAI__Paradigm_7B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |75.47|
|AI2 Reasoning Challenge (25-Shot)|73.63|
|HellaSwag (10-Shot)              |88.66|
|MMLU (5-Shot)                    |64.02|
|TruthfulQA (0-shot)              |75.19|
|Winogrande (5-shot)              |84.53|
|GSM8k (5-shot)                   |66.79|