Instructions to use wangzihaogithub/job-educational-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use wangzihaogithub/job-educational-parser with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="wangzihaogithub/job-educational-parser")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("wangzihaogithub/job-educational-parser", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use wangzihaogithub/job-educational-parser with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "wangzihaogithub/job-educational-parser"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "wangzihaogithub/job-educational-parser",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/wangzihaogithub/job-educational-parser

SGLang

How to use wangzihaogithub/job-educational-parser with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "wangzihaogithub/job-educational-parser" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "wangzihaogithub/job-educational-parser",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "wangzihaogithub/job-educational-parser" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "wangzihaogithub/job-educational-parser",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use wangzihaogithub/job-educational-parser with Docker Model Runner:
```
docker model run hf.co/wangzihaogithub/job-educational-parser
```

wangzihaogithub commited on Aug 13, 2025

Commit

22dfad8

verified ·

1 Parent(s): 7d6a1f7

Update README.md

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@@ -20,12 +20,35 @@ pipeline_tag: text-generation
 # Model Card for output-08-0-0805
 模型任务：输入岗位描述，输出岗位中要求的学历（如 "博士、硕士、本科"）,遵循从高到低
 训练数据：[https://huggingface.co/datasets/wangzihaogithub/job-educational-parser-dataset-08-0-0805](https://huggingface.co/datasets/wangzihaogithub/job-educational-parser-dataset-08-0-0805).
-This model is a fine-tuned version of [None](https://huggingface.co/None).
-It has been trained using [TRL](https://github.com/huggingface/trl).
 ## Quick start

 # Model Card for output-08-0-0805
+This model is a fine-tuned version of [None](https://huggingface.co/None).
+It has been trained using [TRL](https://github.com/huggingface/trl).
 模型任务：输入岗位描述，输出岗位中要求的学历（如 "博士、硕士、本科"）,遵循从高到低
 训练数据：[https://huggingface.co/datasets/wangzihaogithub/job-educational-parser-dataset-08-0-0805](https://huggingface.co/datasets/wangzihaogithub/job-educational-parser-dataset-08-0-0805).
+例如：
+输入
+```json
+{
+  "model": "wangzihaogithub/job-educational-parser",
+  "messages": [
+    {
+      "role": "system",
+      "content": "从岗位中提取学历"
+    },
+    {
+      "role": "user",
+      "content": "游戏美术实习-原画类（26届提供转正）游戏类型&风格：欧美卡通 休闲类游戏 工作职责： 1. 配合各项目组美术需求（包括不限于原画，UI和动画类需求）的落地和整合； 2. 具有比较扎实的手绘能力，能够独立完成运营活动所需的美术设计需求； 3. 通过对主流AI产品的学习，总结提示词使用技巧，通过具体案例验证方法的有效性，协助团队建立规范化的AI应用方法论和完善AI工作流程。 岗位要求： 1.面向游戏/动画/数媒/雕塑/美术/工业设计等设计相关专业； 2.本科及以上学历； 3.2026年应届毕业生； 4.有优秀的绘画基础，会用手绘板，熟练掌握PS等2D设计软件 加分项： 1.美术院校相关专业者优先； 2.爱玩游戏者优先； 3.有相关美术设计实习或者工作经验者优先考虑； 4.性格乐观爽朗，善于表达。"
+    }
+  ],
+  "max_tokens": 32
+}
+```
+输出（固定格式）：博士、硕士、本科
 ## Quick start