Satyr-7B-Model_Stock

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

🧩 Configuration

models:
  - model: NeverSleep/Noromaid-7B-0.4-DPO
  - model: SanjiWatsuki/Kunoichi-DPO-v2-7B
  - model: Undi95/Toppy-M-7B
  - model: Epiculous/Fett-uccine-7B
merge_method: model_stock
base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
dtype: bfloat16

πŸ’» Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "DreadPoor/Satyr-7B-Model_Stock"
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. 71.74
AI2 Reasoning Challenge (25-Shot) 68.60
HellaSwag (10-Shot) 86.96
MMLU (5-Shot) 65.02
TruthfulQA (0-shot) 63.76
Winogrande (5-shot) 80.43
GSM8k (5-shot) 65.66
Downloads last month
124
Safetensors
Model size
7.24B params
Tensor type
BF16
Β·
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 DreadPoor/Satyr-7B-Model_Stock

Quantizations
2 models

Spaces using DreadPoor/Satyr-7B-Model_Stock 5

Evaluation results