mayacinka/ramonda-7b-dpo-ties
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ramonda-7b-dpo-ties
ramonda-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/ramonda-7b-dpo-ties | 76.19 | 72.7 | 89.69| 64.5 | 77.17 | 84.77 | 68.92|
LLM AutoEval | 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