metadata
tags:
- merge
- mergekit
- lazymergekit
- paulml/OGNO-7B
- bardsai/jaskier-7b-dpo-v4.3
base_model:
- paulml/OGNO-7B
- bardsai/jaskier-7b-dpo-v4.3
license: apache-2.0
Buttercup-7b-dpo-ties
Buttercup-7b-dpo-ties is a merge of the following models using LazyMergekit:
Benchmark
Open LLM Leaderboard
| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
|---|---|---|---|---|---|---|---|
| mayacinka/Buttercup-7b-dpo-ties | 76.19 | 72.7 | 89.69 | 64.5 | 77.17 | 84.77 | 68.92 |
🧩 Configuration
models:
- model: bardsai/jaskier-7b-dpo-v5.6
# no parameters necessary for base model
- model: paulml/OGNO-7B
parameters:
density: 0.9
weight: 0.5
- model: bardsai/jaskier-7b-dpo-v4.3
parameters:
density: 0.5
weight: 0.3
merge_method: ties
base_model: bardsai/jaskier-7b-dpo-v5.6
parameters:
normalize: true
dtype: float16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mayacinka/Buttercup-7b-dpo-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"])