pipeline_tag: 文本生成 inference: true widget:

• text: '你好！' example_title: 你好世界 group: Python library_name: transformers

该模型为随机初始化模型，采用deepseek-ai/deepseek-llm-67b-chat的配置但缩小了规模。 注意该模型为float16精度。

代码示例：

import transformers
import torch
import os
from huggingface_hub import create_repo, upload_folder

source_model_id = 'deepseek-ai/deepseek-llm-67b-chat'
save_path = '/tmp/yujiepan/deepseek-llm-tiny-random'
repo_id = 'yujiepan/deepseek-llm-tiny-random'

config = transformers.AutoConfig.from_pretrained(
    source_model_id, trust_remote_code=True)
config.hidden_size = 2
config.intermediate_size = 4
config.num_attention_heads = 2
config.num_hidden_layers = 2
config.num_key_value_heads = 1

model = transformers.AutoModelForCausalLM.from_config(
    config, trust_remote_code=True)
model = model.half()
model.save_pretrained(save_path)

tokenizer = transformers.AutoTokenizer.from_pretrained(
    source_model_id, trust_remote_code=True)
tokenizer.save_pretrained(save_path)

result = transformers.pipelines.pipeline(
    'text-generation',
    model=model.float(), tokenizer=tokenizer)('你好')
print(result)

os.system(f'ls -alh {save_path}')
create_repo(repo_id, exist_ok=True)
upload_folder(repo_id=repo_id, folder_path=save_path)