README.md

metadata

license: apache-2.0
library_name: transformers
tags:
  - mergekit
  - merge
base_model: CultriX/NeuralTrix-7B-dpo
model-index:
  - name: NeuralZephyr-Beagle-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: 68.6
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-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: 86.38
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-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: 64.67
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-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: 65.17
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-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: 81.14
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-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: 63.46
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-7B
          name: Open LLM Leaderboard

merge

This is a merge of pre-trained language models created using mergekit.

Code credit: this excellent medium blog

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using CultriX/NeuralTrix-7B-dpo as a base.

Models Merged

The following models were included in the merge:

• mlabonne/NeuralBeagle14-7B
• HuggingFaceH4/zephyr-7b-alpha

Benchmarks

Open LLM Leaderboard

Model	Average	ARC	HellaSwag	MMLU	TruthfulQA	Winogrande	GSM8K
mayacinka/NeuralZephyr-Beagle-7B	71.57	68.6	86.38	64.67	65.17	81.14	63.46

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: CultriX/NeuralTrix-7B-dpo
  - model: HuggingFaceH4/zephyr-7b-alpha
    parameters:
      density: 0.83
      weight: 0.4
  - model: mlabonne/NeuralBeagle14-7B
    parameters: 
      density: 0.83
      weight: 0.6
merge_method: dare_ties
base_model: CultriX/NeuralTrix-7B-dpo
parameters:
  int8_mask: true
dtype: bfloat16

Inference

# pip install transformers

from transformers import AutoTokenizer
import transformers
import torch

model = "mayacinka/NeuralZephyr-Beagle-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"])

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	71.57
AI2 Reasoning Challenge (25-Shot)	68.60
HellaSwag (10-Shot)	86.38
MMLU (5-Shot)	64.67
TruthfulQA (0-shot)	65.17
Winogrande (5-shot)	81.14
GSM8k (5-shot)	63.46