Deep and foundation models

Model declarations do not download weights or import upstream Python. This example makes named classification specifications only; no pretrained inference or scientific result is produced.

task <- hm_task("class", "classification", "image", "subject_id")
constructors <- list(
  hm_htc, hm_hyperfree, hm_hypersigma, hm_hypervision,
  hm_dual_stream_mhsi, hm_spectralearth, hm_spectralgpt
)
specifications <- lapply(constructors, function(f) f(task))
vapply(specifications, function(x) x$model_id, character(1))
#> [1] "htc"              "hyperfree"        "hypersigma"       "hypervision"     
#> [5] "dual_stream_mhsi" "spectralearth"    "spectralgpt"

HTC, HyperFree and HyperSIGMA have explicit extraction implementations requiring exact reviewed source inventories, weights, preprocessing and rights. Their independent installed-package parity remains pending. HyperSIGMA’s fixed fused features are distinct from its upstream trained downstream model. HyperVision, Dual-Stream-MHSI, SpectralEarth and SpectralGPT retain explicit execution blocks until their exact source/weights/input contracts are admitted. SpectralEarth is an adapted spectral track; SpectralGPT is a lossy multispectral auxiliary track. None is a qualified clinical model.

Package-owned scratch reference IDs use reference: followed by cnn1d, unet2d, cnn3d, spectral_vit, masked_autoencoder, contrastive_encoder, vae, conditional_gan, ddpm, multitask, domain_adversarial or distillation. These have separate training objectives and synthetic gradient, restore and prediction tests. Distillation uses a scratch frozen teacher. Their worker protocol is distinct from the ordinary R engine workflow; registry visibility alone does not admit an R hm_fit() neural route.

Reproduction is opt-in: resolve and review an exact runtime, use explicit training roles/group IDs, bound epochs, retain numeric artifacts and run adapter-specific parity. Do not run a model from a documentation build. GPU/Metal/ROCm/WSL, PEFT, quantization and scientific transfer are not qualified by CPU reference tests. See the runtime article before enabling any external execution.