Llama3.1-SuperHawk-8B
Llama3.1-SuperHawk-8B is a merge of the following models using LazyMergekit:
π§© Configuration
slices:
- sources:
- model: Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base
layer_range: [0, 32]
- model: mukaj/Llama-3.1-Hawkish-8B
layer_range: [0, 32]
merge_method: slerp
base_model: Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base
parameters:
t:
- value: 0.3
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Yuma42/Llama3.1-SuperHawk-8B"
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. | 31.14 |
IFEval (0-Shot) | 79.86 |
BBH (3-Shot) | 31.97 |
MATH Lvl 5 (4-Shot) | 23.49 |
GPQA (0-shot) | 8.39 |
MuSR (0-shot) | 10.38 |
MMLU-PRO (5-shot) | 32.73 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard79.860
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard31.970
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard23.490
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.390
- acc_norm on MuSR (0-shot)Open LLM Leaderboard10.380
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard32.730