ramonda-7b-dpo-ties
ramonda-7b-dpo-ties is a merge of the following models using LazyMergekit:
Benchmark
| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
|---|---|---|---|---|---|---|---|
| mayacinka/ramonda-7b-dpo-ties | 76.19 | 72.7 | 89.69 | 64.5 | 77.17 | 84.77 | 68.92 |
| Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
|---|---|---|---|---|---|
| ramonda-7b-dpo-ties | 44.67 | 77.16 | 77.6 | 49.06 | 62.12 |
🧩 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/ramonda-7b-dpo-ties"
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. | 76.19 |
| AI2 Reasoning Challenge (25-Shot) | 72.70 |
| HellaSwag (10-Shot) | 89.09 |
| MMLU (5-Shot) | 64.50 |
| TruthfulQA (0-shot) | 77.17 |
| Winogrande (5-shot) | 84.77 |
| GSM8k (5-shot) | 68.92 |