NeuralPipe-7B-slerp
NeuralPipe-7B-slerp is a merge of the following models using LazyMergekit:
- RaduGabriel/MUZD
- RaduGabriel/Mistral-Instruct-Ukrainian-SFT
- Radu1999/MisterUkrainianDPO
- CultriX/NeuralTrix-7B-dpo
🧩 Configuration
models:
- model: RaduGabriel/MUZD
parameters:
weight: 0.3
- model: RaduGabriel/Mistral-Instruct-Ukrainian-SFT
parameters:
weight: 0.3
- model: Radu1999/MisterUkrainianDPO
parameters:
weight: 0.1
- model: CultriX/NeuralTrix-7B-dpo
parameters:
weight: 0.3
merge_method: task_arithmetic
base_model: mistralai/Mistral-7B-v0.1
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "RaduGabriel/SirUkrainian"
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.bfloat16,
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. | 70.50 |
AI2 Reasoning Challenge (25-Shot) | 67.32 |
HellaSwag (10-Shot) | 85.54 |
MMLU (5-Shot) | 63.14 |
TruthfulQA (0-shot) | 68.74 |
Winogrande (5-shot) | 81.53 |
GSM8k (5-shot) | 56.71 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard67.320
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard85.540
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard63.140
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard68.740
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard81.530
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard56.710