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Saylor Innovations HuggingFace Model Detail
x402
Saylor Innovations HuggingFace Model Detail is a paid API for AI agents from saylorinnovations.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
Fetches detailed metadata for a Hugging Face model by its hub ID, including license, parameter count, precision, downloads, likes, gated status, base model, languages, weight files, and tags.
Price / call$0.01
Success—
StatusUnknown
How this service works
Hugging Face model detail by id - licence, parameter count and precision, downloads, likes, gated status, base model, languages, weight files and tags
Output
Returns a JSON object containing the model's hub ID, canonical URL, author, license identifier, total parameter count, parameter types/precision, 30-day download count, likes, gated status, privacy status, base model, supported languages, ML task, library, number of files, number of weight files, tags, creation date, and last modified date.
Example use cases
Checking model license before deployment
“Before we use openai/whisper-large-v3 in our product, can you look it up on Hugging Face and tell me what license it has and whether it's gated?”
Comparing model sizes for hardware planning
“I'm trying to decide between a few models — can you look up meta-llama/Llama-3.1-8B on Hugging Face and tell me the total parameter count, precision types, and how many weight files it has?”
Assessing model popularity and activity
“How popular is mistralai/Mistral-7B-Instruct-v0.3 on Hugging Face? I want to know its download count over the last 30 days, total likes, when it was last modified, and who the author is.”
Technical details
Endpoint
GEThttps://saylorinnovations.com/api/ai/hf-model?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need structured, machine-readable metadata about a specific Hugging Face model — particularly license, parameters, and download stats — without scraping the HuggingFace website or using the raw HF API directly. Ideal for agents doing model selection, compliance checks, or capability assessments that need clean JSON output at low cost.
Side effects
- Invalid or non-existent model ID returns an error or empty result
- Model ID must be in 'org/name' format — bare model names without org prefix may fail
- Private or restricted models may return limited metadata
- Network timeouts if Hugging Face Hub is slow or unavailable
- Gated models may not expose all fields without appropriate credentials
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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