README.md

---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- eren23/slerp-test-turdus-beagle
- udkai/Turdus
- 222gate/BrurryDog-7b-v0.1
base_model:
- eren23/slerp-test-turdus-beagle
- udkai/Turdus
- 222gate/BrurryDog-7b-v0.1
model-index:
- name: bleagle-7b-v0.1-test
  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: 72.27
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/bleagle-7b-v0.1-test
      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: 88.24
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/bleagle-7b-v0.1-test
      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: 64.37
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/bleagle-7b-v0.1-test
      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: 67.83
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/bleagle-7b-v0.1-test
      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: 85.48
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/bleagle-7b-v0.1-test
      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: 65.13
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/bleagle-7b-v0.1-test
      name: Open LLM Leaderboard
---

# bleagle-7b-v0.1-test

bleagle-7b-v0.1-test is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [eren23/slerp-test-turdus-beagle](https://huggingface.co/eren23/slerp-test-turdus-beagle)
* [udkai/Turdus](https://huggingface.co/udkai/Turdus)
* [222gate/BrurryDog-7b-v0.1](https://huggingface.co/222gate/BrurryDog-7b-v0.1)

## 🧩 Configuration

```yaml
models:
  - model: eren23/slerp-test-turdus-beagle
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: udkai/Turdus
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
  - model: 222gate/BrurryDog-7b-v0.1
    parameters:
      density: 0.33
      weight:
        - filter: mlp
          value: 0.5
        - value: 0
merge_method: dare_ties
base_model: leveldevai/MarcBeagle-7B
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16
embed_slerp: true
tokenizer_source: union
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "222gate/bleagle-7b-v0.1-test"
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](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_222gate__bleagle-7b-v0.1-test)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |73.89|
|AI2 Reasoning Challenge (25-Shot)|72.27|
|HellaSwag (10-Shot)              |88.24|
|MMLU (5-Shot)                    |64.37|
|TruthfulQA (0-shot)              |67.83|
|Winogrande (5-shot)              |85.48|
|GSM8k (5-shot)                   |65.13|