NeMoTrix-v2

NeMoTrix-v2 is a merge of the following models using LazyMergekit:

• mlabonne/AlphaMonarch-7B
• mlabonne/NeuralMonarch-7B
• Kukedlc/NeuralMaxime-7B-slerp
• eren23/dpo-binarized-NeuralTrix-7B

🧩 Configuration

models:
  - model: CultriX/MonaTrix-v4
    # No parameters necessary for base model, chosen for its strong performance and presence in high-scoring configurations
  - model: mlabonne/AlphaMonarch-7B
    parameters:
      density: 0.65
      weight: 0.4
  - model: mlabonne/NeuralMonarch-7B
    parameters:
      density: 0.65
      weight: 0.35
  - model: Kukedlc/NeuralMaxime-7B-slerp
    parameters:
      density: 0.6
      weight: 0.35
  - model: eren23/dpo-binarized-NeuralTrix-7B
    parameters:
      density: 0.55
      weight: 0.25
merge_method: dare_ties
base_model: CultriX/MonaTrix-v4
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "CultriX/NeMoTrix-v2"
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"])