Bloslain-8B-v0.2

Bloslain-8B-v0.2 is a merge of the following models using LazyMergekit:

• BlackBeenie/Neos-Llama-3.1-8B
• Solshine/Meta-Llama-3.1-8B-Instruct-Python-Coder
• Solshine/reflection-llama-3.1-8B

🧩 Configuration

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

!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

Detailed results can be found here

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