WestOrcaNeuralMarco-DPO-v2-DARETIES-7B

WestOrcaNeuralMarco-DPO-v2-DARETIES-7B

WestOrcaNeuralMarco-DPO-v2-DARETIES-7B is a merge of the following models using LazyMergekit:

• senseable/Westlake-7B-v2
• decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP
• mlabonne/NeuralMarcoro14-7B

🧩 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