KuTrix-7b

This is a merge of pre-trained language models created using mergekit.

Quantized versions :

• GGUF

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using mistralai/Mistral-7B-v0.1 as a base.

Models Merged

The following models were included in the merge:

• SanjiWatsuki/Kunoichi-DPO-v2-7B
• CultriX/NeuralTrix-7B-dpo

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: mistralai/Mistral-7B-v0.1
    # No parameters necessary for base model
  - model: SanjiWatsuki/Kunoichi-DPO-v2-7B
    parameters:
      weight: 0.49
      density: 0.6
  - model: CultriX/NeuralTrix-7B-dpo
    parameters:
      weight: 0.4
      density: 0.6
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16

Usage Example

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "seyf1elislam/KuTrix-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

Metric	Value
Avg.	74.42
AI2 Reasoning Challenge (25-Shot)	70.48
HellaSwag (10-Shot)	87.94
MMLU (5-Shot)	65.28
TruthfulQA (0-shot)	70.85
Winogrande (5-shot)	81.93
GSM8k (5-shot)	70.05