README.md

---
tags:
- merge
- mergekit
- lazymergekit
- BlackBeenie/Neos-Llama-3.1-8B
- Solshine/Meta-Llama-3.1-8B-Instruct-Python-Coder
- Solshine/reflection-llama-3.1-8B
base_model:
- BlackBeenie/Neos-Llama-3.1-8B
- Solshine/Meta-Llama-3.1-8B-Instruct-Python-Coder
- Solshine/reflection-llama-3.1-8B
model-index:
- name: Bloslain-8B-v0.2
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 50.23
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BlackBeenie/Bloslain-8B-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 30.66
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BlackBeenie/Bloslain-8B-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 14.5
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BlackBeenie/Bloslain-8B-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 7.49
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BlackBeenie/Bloslain-8B-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 10.45
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BlackBeenie/Bloslain-8B-v0.2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 29.48
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BlackBeenie/Bloslain-8B-v0.2
      name: Open LLM Leaderboard
---

# Bloslain-8B-v0.2

Bloslain-8B-v0.2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [BlackBeenie/Neos-Llama-3.1-8B](https://huggingface.co/BlackBeenie/Neos-Llama-3.1-8B)
* [Solshine/Meta-Llama-3.1-8B-Instruct-Python-Coder](https://huggingface.co/Solshine/Meta-Llama-3.1-8B-Instruct-Python-Coder)
* [Solshine/reflection-llama-3.1-8B](https://huggingface.co/Solshine/reflection-llama-3.1-8B)

## 🧩 Configuration

```yaml
models:
  - model: NousResearch/Meta-Llama-3.1-8B-Instruct
    # No parameters necessary for base model
  - model: BlackBeenie/Neos-Llama-3.1-8B
    parameters:
      density: 0.53
      weight: 0.4
  - model: Solshine/Meta-Llama-3.1-8B-Instruct-Python-Coder
    parameters:
      density: 0.53
      weight: 0.3
  - model: Solshine/reflection-llama-3.1-8B
    parameters:
      density: 0.53
      weight: 0.3
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3.1-8B-Instruct
parameters:
  int8_mask: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "BlackBeenie/Bloslain-8B-v0.2"
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/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_BlackBeenie__Bloslain-8B-v0.2)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |23.80|
|IFEval (0-Shot)    |50.23|
|BBH (3-Shot)       |30.66|
|MATH Lvl 5 (4-Shot)|14.50|
|GPQA (0-shot)      | 7.49|
|MuSR (0-shot)      |10.45|
|MMLU-PRO (5-shot)  |29.48|