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Kukedlc/NeuralMaths-Experiment-7b
NeuralMaths-Experiment-7b is a text generation model from Kukedlc. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
<div style="font-size: 42px; text-align: center;"🤖 NeuralMaths-Experiment-7b 🤖</div
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From the Hugging Face model README

NeuralMaths-Experiment-7b is a merge of the following models using LazyMergekit:
models:
- model: Kukedlc/NeuralSirKrishna-7b
# No parameters necessary for base model
- model: WizardLM/WizardMath-7B-V1.1
parameters:
density: 0.66
weight: 0.2
- model: mlabonne/NeuralDaredevil-7B
parameters:
density: 0.55
weight: 0.2
- model: Kukedlc/Neural4gsm8k
parameters:
density: 0.55
weight: 0.2
- model: Eric111/Mayo
parameters:
density: 0.44
weight: 0.2
- model: Kukedlc/NeuralSirKrishna-7b
parameters:
density: 0.66
weight: 0.2
merge_method: dare_ties
base_model: Kukedlc/NeuralSirKrishna-7b
parameters:
int8_mask: true
dtype: bfloat16
🌳 Model Family Tree

!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/NeuralMaths-Experiment-7b"
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"])
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 73.95 |
| AI2 Reasoning Challenge (25-Shot) | 69.71 |
| HellaSwag (10-Shot) | 87.48 |
| MMLU (5-Shot) | 65.01 |
| TruthfulQA (0-shot) | 63.83 |
| Winogrande (5-shot) | 82.48 |
| GSM8k (5-shot) | 75.21 |