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 |
- Downloads last month
- 12
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for allknowingroger/MixTAO-19B-pass
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