Model HfHub

ml/repos/hf::HfHub

Parameters

↳ const cache_dir: string = ""
↳ const endpoint: string = "https://huggingface.co"
↳ const repo_id: string
↳ const repo_type: string = "model"
↳ const revision: string = "main"
↳ const token: string = ""

HuggingFace Hub repository configuration.

Holds the connection and repository parameters needed to reach a repository on the HuggingFace Hub. Does no work by itself; use the fetch treatment to trigger the actual resolution and download of files.

• repo_id: repository identifier, e.g. "mistralai/Mistral-7B-v0.1".
• repo_type: "model" (default), "dataset", or "space".
• revision: git revision to pin: branch, tag, or commit hash (default "main").
• endpoint: Hub API base URL (default "https://huggingface.co"; override for mirrors).
• cache_dir: local cache directory (empty string uses the default ~/.cache/huggingface/hub).
• token: HuggingFace access token for private repositories (empty string means no token).

ℹ️ Use HfHub together with fetch: HfHub holds the configuration while fetch performs the actual network and cache operations when triggered.

use ml/repos/hf::HfHub
use ml/repos/hf::fetch
use ml/models/mistral::Mistral
use ml/models/mistral::load
use std/engine/util::startup

treatment example()
  model hub:    HfHub(repo_id = "mistralai/Mistral-7B-v0.1")
  model mistral: Mistral()
{
    startup()
    fetch[hub=hub]()
    load[mistral=mistral]()

    startup.trigger   -> fetch.trigger
    fetch.safetensors -> load.safetensors
    fetch.tokenizer   -> load.tokenizer
}