README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - mlabonne/OmniBeagle-7B
  - flemmingmiguel/MBX-7B-v3
  - AiMavenAi/AiMaven-Prometheus
base_model:
  - mlabonne/OmniBeagle-7B
  - flemmingmiguel/MBX-7B-v3
  - AiMavenAi/AiMaven-Prometheus
license: apache-2.0

Edit: As of 2024-02-10 this is currently the best performing 7B model on both the Open-LLM-Leaderboard as well as this (Nous Benchmark) Leaderboard

NeuralTrix-7B-v1

NeuralTrix-7B-v1 is a merge of the following models using LazyMergekit:

• mlabonne/OmniBeagle-7B
• flemmingmiguel/MBX-7B-v3
• AiMavenAi/AiMaven-Prometheus

🧩 Configuration

models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: mlabonne/OmniBeagle-7B
    parameters:
      density: 0.65
      weight: 0.4
  - model: flemmingmiguel/MBX-7B-v3
    parameters:
      density: 0.6
      weight: 0.35
  - model: AiMavenAi/AiMaven-Prometheus
    parameters:
      density: 0.6
      weight: 0.35
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "CultriX/NeuralTrix-7B-v1"
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"])