Edit model card

StrangeMerges_9-7B-dare_ties

StrangeMerges_9-7B-dare_ties is a merge of the following models using LazyMergekit:

🧩 Configuration

models:
  - model: Gille/StrangeMerges_8-7B-slerp
    # no parameters necessary for base model
  - model: leveldevai/TurdusBeagle-7B
    parameters:
      density: 0.5
      weight: 0.4
  - model: samir-fama/FernandoGPT-v1
    parameters:
      density: 0.5
      weight: 0.6
merge_method: dare_ties
base_model: Gille/StrangeMerges_8-7B-slerp
parameters:
  normalize: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Gille/StrangeMerges_9-7B-dare_ties"
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. 73.32
AI2 Reasoning Challenge (25-Shot) 70.31
HellaSwag (10-Shot) 87.46
MMLU (5-Shot) 65.08
TruthfulQA (0-shot) 65.08
Winogrande (5-shot) 81.37
GSM8k (5-shot) 70.58
Downloads last month
79
Safetensors
Model size
7.24B params
Tensor type
FP16
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Gille/StrangeMerges_9-7B-dare_ties

Evaluation results