WestOrcaNeuralMarco-DPO-v2-DARETIES-7B
WestOrcaNeuralMarco-DPO-v2-DARETIES-7B is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: mistralai/Mistral-7B-v0.1
# No parameters necessary for base model
- model: senseable/Westlake-7B-v2
parameters:
density: 0.73
weight: 0.4
- model: decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP
parameters:
density: 0.55
weight: 0.3
- model: mlabonne/NeuralMarcoro14-7B
parameters:
density: 0.45
weight: 0.3
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-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"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 73.98 |
| AI2 Reasoning Challenge (25-Shot) | 71.93 |
| HellaSwag (10-Shot) | 88.06 |
| MMLU (5-Shot) | 64.99 |
| TruthfulQA (0-shot) | 65.96 |
| Winogrande (5-shot) | 82.79 |
| GSM8k (5-shot) | 70.13 |