VOOZH about

URL: https://huggingface.co/shadowml/DareBeagle-7B

⇱ shadowml/DareBeagle-7B · Hugging Face


DareBeagle-7B

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

🧩 Configuration

slices:
 - sources:
 - model: mlabonne/NeuralBeagle14-7B
 layer_range: [0, 32]
 - model: mlabonne/NeuralDaredevil-7B
 layer_range: [0, 32]
merge_method: slerp
base_model: mlabonne/NeuralDaredevil-7B
parameters:
 t:
 - filter: self_attn
 value: [0, 0.5, 0.3, 0.7, 1]
 - filter: mlp
 value: [1, 0.5, 0.7, 0.3, 0]
 - value: 0.45 # fallback for rest of tensors
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "shadowml/DareBeagle-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. 74.58
AI2 Reasoning Challenge (25-Shot) 71.67
HellaSwag (10-Shot) 88.01
MMLU (5-Shot) 65.03
TruthfulQA (0-shot) 68.98
Winogrande (5-shot) 82.32
GSM8k (5-shot) 71.49
Downloads last month
99
Safetensors
Model size
7B params
Tensor type
F16
·

Model tree for shadowml/DareBeagle-7B

Quantizations
2 models

Spaces using shadowml/DareBeagle-7B 16

Evaluation results