MixTAO-19B-pass
MixTAO-19B-pass is a merge of the following models using LazyMergekit:
🧩 Configuration
slices:
- sources:
- model: zhengr/MixTAO-7Bx2-MoE-v8.1
layer_range: [0, 24]
- sources:
- model: zhengr/MixTAO-7Bx2-MoE-v8.1
layer_range: [8, 32]
merge_method: passthrough
dtype: float16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "allknowingroger/MixTAO-19B-pass"
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. | 20.54 |
| IFEval (0-Shot) | 38.14 |
| BBH (3-Shot) | 31.58 |
| MATH Lvl 5 (4-Shot) | 5.59 |
| GPQA (0-shot) | 4.59 |
| MuSR (0-shot) | 19.95 |
| MMLU-PRO (5-shot) | 23.39 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard38.140
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard31.580
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard5.590
- acc_norm on GPQA (0-shot)Open LLM Leaderboard4.590
- acc_norm on MuSR (0-shot)Open LLM Leaderboard19.950
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard23.390