models:
  - model: Qwen/Qwen2.5-14B-Instruct-1M
  - model: nvidia/OpenReasoning-Nemotron-14B
base_model: VortexHunter23/LeoPARD-Coder-0.8.5-pt1
merge_method: model_stock
parameters:
  normalize: true
dtype: bfloat16

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "VortexHunter23/LeoPARD-Coder-0.8.5-pt1"

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"])

VortexHunter23/LeoPARD-Coder-0.8.5-pt1.1

LeoPARD-Coder-0.8.5-pt1

🧩 Configuration

💻 Usage

VortexHunter23/
LeoPARD-Coder-0.8.5-pt1.1