Merge-Mixtral-Prometheus-8x7B
Merge-Mixtral-Prometheus-8x7B is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: prometheus-eval/prometheus-8x7b-v2.0
parameters:
weight: 1.0
- model: mistralai/Mixtral-8x7B-Instruct-v0.1
parameters:
weight: 1.0
merge_method: linear
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "vicgalle/test-merge-3"
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"])
Paper citation
Paper: https://arxiv.org/abs/2406.07188
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 24.61 |
IFEval (0-Shot) | 57.44 |
BBH (3-Shot) | 34.65 |
MATH Lvl 5 (4-Shot) | 8.31 |
GPQA (0-shot) | 7.83 |
MuSR (0-shot) | 9.59 |
MMLU-PRO (5-shot) | 29.82 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard57.440
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard34.650
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard8.310
- acc_norm on GPQA (0-shot)Open LLM Leaderboard7.830
- acc_norm on MuSR (0-shot)Open LLM Leaderboard9.590
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard29.820