Assets

Workspace › Assets is where your datasets, model weights, LoRAs, configs, and job outputs live. One place, one list, shared by everyone in the workspace — the same asset can feed a Pod, a task, or a download.

Assets and files

Layer	What it is	What you see
Asset	A named set of files — “cat-lora”, “training-set-v2”	One row in the list
File	One file inside the asset, with its relative path	The file list in the detail drawer

Uploading a folder produces one asset with many files, not many assets — directory checkpoint formats stay intact.

How files are added

• Uploading a folder or adding files puts them into the asset. Adding a file at a path that already exists in the asset is rejected as a collision — pick a different path, or a new asset.
• A Pod harvesting the same folder name keeps syncing into the same asset. New files are added; a file with a path the asset already has is replaced by the newer copy. A file your training script rotates away on the Pod’s disk stays in the asset — harvest only adds and replaces, it never deletes.
• A different Pod, task run, or upload that produces the same name gets its own asset, with a -2 suffix (-3, and so on) — the suffix applies only while an asset with the earlier name still exists; delete it and the name is free again. Meshive no longer prompts you to merge same-named assets from different origins.
• Renaming an asset is free and doesn’t touch its files. Because the name is what a Pod keeps writing to, a Pod that keeps writing the old directory name starts a fresh asset after a rename — that’s intentional.
• Uploading or harvesting doesn’t remove a file from an asset on its own. Writing to a path the asset already has replaces what’s stored there; it never drops a file outright. To keep several revisions of something around side by side, give them different file names or put them in differently named assets.

Types

Each asset carries a type — dataset, model, adapter (LoRA), checkpoint, output, config, or file. It is a hint, not a rule: it drives filtering and the default mount location when you attach the asset. Meshive guesses from the file extensions (or from the template’s declaration for harvested output), and you can correct it in the detail drawer.

Badges

Badge	Meaning	What to do
pickle · runs code on load	The file is a Python pickle format (.pkl, .joblib, .pth, some .bin) — loading it executes code. detected means we read the file header and confirmed it; suspected means we inferred it from the name	Only load assets you trust. Prefer safetensors when the publisher offers it
format not verified	The file has no extension, so we can’t say what it is	Neutral — common in directory checkpoint trees
in use	A running Pod or a non-terminal task is consuming this asset	Delete is blocked until it’s released
frozen	The asset is under abuse review (Terms §10)	Everything except metadata edits is locked
M / S3	Stored in Meshive-managed storage / registered in your own bucket	Only M bytes are billed as asset storage

Where the bytes live

Storage	Created by	Billed	Deleted by Meshive
Managed	Web upload, Pod harvest, task output, imports, subset fetches	Yes — per GB·month (details)	Yes, when you delete it or when the unpaid-balance lifecycle runs
Your bucket	In-place registration and prefix references (details)	No — you already pay your provider	Never. We only read

Deleting

Deleting an asset removes it from the list and stops storage charges immediately. Managed bytes are then physically removed by a background cleanup pass; objects in your own bucket are left untouched.

• Delete is blocked (409) while a Pod or task is using the asset — for a harvested asset, that includes its owning Pod still running (and able to harvest into it again). Stop or finish the workload first.
• A failed upload is removed the same way, by deleting the asset — there’s no separate “discard” action; the same in-use rule applies.
• Individual files can be removed from the file views without deleting the whole asset. Deleting the asset itself removes all of its files.
• Deletion is not recoverable. Download or export anything you want to keep.

Where to go next

• Getting data in — upload, harvest from a Pod, import from Hugging Face or CivitAI, register or reference data in your own bucket.
• Using assets — attach to a Pod, inject into a running Pod, feed a task, download or export.
• Billing, limits & safety — what storage costs, what happens when credit runs out, and the abuse-report flow.