🚀 StrangeMerges_17-7B-dare_ties
StrangeMerges_17-7B-dare_ties是一个通过合并多个模型得到的模型。它借助LazyMergekit工具,将不同模型的优势融合,为文本生成任务提供了更强大的能力。
🚀 快速开始
安装依赖
!pip install -qU transformers accelerate
代码示例
from transformers import AutoTokenizer
import transformers
import torch
model = "Gille/StrangeMerges_17-7B-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"])
✨ 主要特性
StrangeMerges_17-7B-dare_ties模型通过合并以下两个模型构建而成:
📦 安装指南
使用前需要安装transformers
和accelerate
库,可以使用以下命令进行安装:
!pip install -qU transformers accelerate
💻 使用示例
基础用法
from transformers import AutoTokenizer
import transformers
import torch
model = "Gille/StrangeMerges_17-7B-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"])
📚 详细文档
🧩 配置信息
models:
- model: Gille/StrangeMerges_16-7B-slerp
- model: Gille/StrangeMerges_16-7B-slerp
parameters:
density: 0.5
weight: 0.4
- model: Gille/StrangeMerges_12-7B-slerp
parameters:
density: 0.5
weight: 0.6
merge_method: dare_ties
base_model: Gille/StrangeMerges_16-7B-slerp
parameters:
normalize: true
dtype: float16
详细结果可查看此处
指标 |
值 |
平均值 |
69.54 |
AI2推理挑战 (25次少样本学习) |
66.64 |
HellaSwag (10次少样本学习) |
86.04 |
MMLU (5次少样本学习) |
65.07 |
TruthfulQA (0次少样本学习) |
53.18 |
Winogrande (5次少样本学习) |
81.93 |
GSM8k (5次少样本学习) |
64.37 |
📄 许可证
本项目采用Apache-2.0许可证。