YamMaths-7B-slerp
YamMaths-7B-slerp is a merge of the following models using LazyMergekit:
🧩 Configuration
slices:
- sources:
- model: automerger/YamshadowExperiment28-7B
layer_range: [0, 32]
- model: Kukedlc/NeuralMaths-Experiment-7b
layer_range: [0, 32]
merge_method: slerp
base_model: automerger/YamshadowExperiment28-7B
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "allknowingroger/YamMaths-7B-slerp"
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. | 20.38 |
IFEval (0-Shot) | 41.48 |
BBH (3-Shot) | 32.13 |
MATH Lvl 5 (4-Shot) | 7.48 |
GPQA (0-shot) | 4.03 |
MuSR (0-shot) | 13.46 |
MMLU-PRO (5-shot) | 23.68 |
- Downloads last month
- 6
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for allknowingroger/YamMaths-7B-slerp
Merge model
this model
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard41.480
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard32.130
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard7.480
- acc_norm on GPQA (0-shot)Open LLM Leaderboard4.030
- acc_norm on MuSR (0-shot)Open LLM Leaderboard13.460
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard23.680