[
{
"id": "huggingface-models-api_1000",
"service": "huggingface-models-api",
"title": "HUGGINGFACE MODELS Record #1",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for huggingface-models-api",
"inputReceived": {
"pipelineTag": "text-generation",
"sort": "downloads",
"searchQuery": "",
"limit": 25
},
"data": {
"index": 1,
"relevanceScore": 0.95,
"summary": "High-fidelity structured response for HUGGINGFACE MODELS query parameter extraction.",
"attributes": {
"region": "Global",
"category": "HUGGINGFACE",
"timestamp": "2026-10-12T10:23:37.104Z"
}
},
"timestamp": "2026-10-12T10:23:37.104Z"
},
{
"id": "huggingface-models-api_1001",
"service": "huggingface-models-api",
"title": "HUGGINGFACE MODELS Record #2",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for huggingface-models-api",
"inputReceived": {
"pipelineTag": "text-generation",
"sort": "downloads",
"searchQuery": "",
"limit": 25
},
"data": {
"index": 2,
"relevanceScore": 0.8999999999999999,
"summary": "High-fidelity structured response for HUGGINGFACE MODELS query parameter extraction.",
"attributes": {
"region": "Global",
"category": "HUGGINGFACE",
"timestamp": "2026-10-12T10:23:37.104Z"
}
},
"timestamp": "2026-10-12T10:23:37.104Z"
},
{
"id": "huggingface-models-api_1002",
"service": "huggingface-models-api",
"title": "HUGGINGFACE MODELS Record #3",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for huggingface-models-api",
"inputReceived": {
"pipelineTag": "text-generation",
"sort": "downloads",
"searchQuery": "",
"limit": 25
},
"data": {
"index": 3,
"relevanceScore": 0.85,
"summary": "High-fidelity structured response for HUGGINGFACE MODELS query parameter extraction.",
"attributes": {
"region": "Global",
"category": "HUGGINGFACE",
"timestamp": "2026-10-12T10:23:37.104Z"
}
},
"timestamp": "2026-10-12T10:23:37.104Z"
},
{
"id": "huggingface-models-api_1003",
"service": "huggingface-models-api",
"title": "HUGGINGFACE MODELS Record #4",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for huggingface-models-api",
"inputReceived": {
"pipelineTag": "text-generation",
"sort": "downloads",
"searchQuery": "",
"limit": 25
},
"data": {
"index": 4,
"relevanceScore": 0.7999999999999999,
"summary": "High-fidelity structured response for HUGGINGFACE MODELS query parameter extraction.",
"attributes": {
"region": "Global",
"category": "HUGGINGFACE",
"timestamp": "2026-10-12T10:23:37.104Z"
}
},
"timestamp": "2026-10-12T10:23:37.104Z"
},
{
"id": "huggingface-models-api_1004",
"service": "huggingface-models-api",
"title": "HUGGINGFACE MODELS Record #5",
"status": "VERIFIED_ACTIVE",
"result": "Processed query successfully for huggingface-models-api",
"inputReceived": {
"pipelineTag": "text-generation",
"sort": "downloads",
"searchQuery": "",
"limit": 25
},
"data": {
"index": 5,
"relevanceScore": 0.75,
"summary": "High-fidelity structured response for HUGGINGFACE MODELS query parameter extraction.",
"attributes": {
"region": "Global",
"category": "HUGGINGFACE",
"timestamp": "2026-10-12T10:23:37.104Z"
}
},
"timestamp": "2026-10-12T10:23:37.104Z"
}
]
curl --location --request POST 'https://zylalabs.com/api/14172/hugging+face+ai+models+datasets+and+spaces+scraper+api/35216/execute+hugging+face+ai+models+datasets+and+spaces+scraper+api' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{"pipelineTag":"text-generation","sort":"downloads","searchQuery":"","limit":25}'
注册后,每个开发者都会被分配一个个人 API 访问密钥,这是一个唯一的字母和数字组合,用于访问我们的 API 端点。要使用 Hugging Face AI 模型 数据集 和 空间 抓取器 API 进行身份验证,只需在 Authorization 标头中包含您的 bearer token。
| 标头 | 描述 |
|---|---|
授权
|
必需
应为 Bearer access_key. 订阅后,请查看上方的"您的 API 访问密钥"。
|
无长期承诺。随时升级、降级或取消。 免费试用包括最多 50 个请求。
(年度计费可节省 2 个月 🎉)
该端点返回关于Hugging Face的AI模型、数据集和空间的详细元数据 这包括模型架构、性能指标、心脏计数、管道标签(例如NLP、视觉、音频)和许可证类型等属性
响应中的关键字段包括"id"、"title"、"status"、"result"、"inputReceived"和"data"。"data"字段包含"relevanceScore"、"summary"和"timestamp"等属性,提供有关模型性能和特征的洞察
返回的数据结构为JSON数组,每个条目代表一个模型或数据集。每个条目包含“inputReceived”和“data”的嵌套对象,允许组织访问各种属性和指标
该端点提供有关模型架构、性能指标、下载次数、可用次数、管道标签、许可证类型和使用示例的信息,便利对Hugging Face资源的全面分析
用户可以通过指定“pipelineTag”、“sort”、“searchQuery”和“limit”等参数来自定义请求。这允许根据用户定义的标准检索特定模型或数据集的定制查询
响应数据被组织为一个对象列表,每个对象包含关于特定模型或数据集的元数据 每个对象包括用于识别 状态 输入参数和详细属性的字段 使得解析和分析变得容易
数据直接来源于Hugging Face平台,该平台聚合了来自众多开发者和研究人员的贡献。这确保了机器学习模型和数据集的多样性和综合性
典型的用例包括发现相关的数据集用于训练机器学习模型 微调现有模型 以及将Hugging Face资源集成到自然语言处理 计算机视觉和音频分析的应用中