README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - mlabonne/AlphaMonarch-7B
  - Kukedlc/NeuralMaxime-7B-slerp
  - bardsai/jaskier-7b-dpo-v5.6
base_model:
  - mlabonne/AlphaMonarch-7B
  - Kukedlc/NeuralMaxime-7B-slerp
  - bardsai/jaskier-7b-dpo-v5.6
license: apache-2.0

MonaTrix-v6

MonaTrix-v6 is a merge of the following models using LazyMergekit:

• mlabonne/AlphaMonarch-7B
• Kukedlc/NeuralMaxime-7B-slerp
• bardsai/jaskier-7b-dpo-v5.6

🧩 Configuration

models:
  - model: eren23/dpo-binarized-NeutrixOmnibe-7B
    # No parameters necessary for base model
  - model: mlabonne/AlphaMonarch-7B
    #Emphasize the beginning of Vicuna format models
    parameters:
      weight: 0.6
      density: 0.59
  - model: Kukedlc/NeuralMaxime-7B-slerp
    parameters:
      weight: 0.1
      density: 0.55
  # Vicuna format
  - model: bardsai/jaskier-7b-dpo-v5.6
    parameters:
      weight: 0.3
      density: 0.55

merge_method: dare_ties
base_model: eren23/dpo-binarized-NeutrixOmnibe-7B
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/MonaTrix-v6"
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"])