This repository contains the wound-specific adapter delta used to adapt the 7B Large Vision Model (LVM) for longitudinal porcine wound image extrapolation.
The artifact is not a standalone model checkpoint. It contains only the 84 project-trained adapter tensors. Users must obtain the matching LVM base checkpoint and VQ image tokenizer separately.
| Field | Value |
|---|---|
| File | wound_llama_adapter_delta_v1.pth |
| Format | wound_forecasting_adapter_delta_v1 |
| Size | 33,786,121 bytes |
| Adapter tensors | 84 |
| Base model | Emma02/LVM_ckpts |
| VQ tokenizer | Emma02/vqvae_ckpts |
The upstream base-model and VQ-tokenizer weights are not mirrored in this repository.
Construct the matching LVM adapter architecture from the upstream base checkpoint before applying this delta.
import torch
from huggingface_hub import hf_hub_download
from wound_forecasting.llama_adapter import (
load_adapter_delta,
)
adapter_path = hf_hub_download(
repo_id="bridenmj/wound-llama-adapter",
filename="wound_llama_adapter_delta_v1.pth",
)
adapter_package = torch.load(
adapter_path,
map_location="cpu",
weights_only=False,
)
load_adapter_delta(
model,
adapter_package,
expected_base_model="Emma02/LVM_ckpts",
)
model.eval()
The exact construction parameters are recorded in
adapter_config.json.
The model was trained on processed longitudinal images derived from the public porcine wound-healing dataset:
This repository distributes only the project-trained adapter delta. It does not redistribute the upstream LVM base model or VQ tokenizer.
The original project-trained weights released in this repository are licensed under the Creative Commons Attribution–NonCommercial 4.0 International license (CC BY-NC 4.0).
Third-party implementations, base models, tokenizers, and other external dependencies are not relicensed by this repository and remain subject to their respective licenses and terms. Any upstream license or notice files included in this repository continue to apply to the corresponding upstream materials.
4 commits
This repository contains the wound-specific adapter delta used to adapt the 7B Large Vision Model (LVM) for longitudinal porcine wound image extrapolation.
The artifact is not a standalone model checkpoint. It contains only the 84 project-trained adapter tensors. Users must obtain the matching LVM base checkpoint and VQ image tokenizer separately.
| Field | Value |
|---|---|
| File | wound_llama_adapter_delta_v1.pth |
| Format | wound_forecasting_adapter_delta_v1 |
| Size | 33,786,121 bytes |
| Adapter tensors | 84 |
| Base model | Emma02/LVM_ckpts |
| VQ tokenizer | Emma02/vqvae_ckpts |
The upstream base-model and VQ-tokenizer weights are not mirrored in this repository.
Construct the matching LVM adapter architecture from the upstream base checkpoint before applying this delta.
import torch
from huggingface_hub import hf_hub_download
from wound_forecasting.llama_adapter import (
load_adapter_delta,
)
adapter_path = hf_hub_download(
repo_id="bridenmj/wound-llama-adapter",
filename="wound_llama_adapter_delta_v1.pth",
)
adapter_package = torch.load(
adapter_path,
map_location="cpu",
weights_only=False,
)
load_adapter_delta(
model,
adapter_package,
expected_base_model="Emma02/LVM_ckpts",
)
model.eval()
The exact construction parameters are recorded in
adapter_config.json.
The model was trained on processed longitudinal images derived from the public porcine wound-healing dataset:
This repository distributes only the project-trained adapter delta. It does not redistribute the upstream LVM base model or VQ tokenizer.
The original project-trained weights released in this repository are licensed under the Creative Commons Attribution–NonCommercial 4.0 International license (CC BY-NC 4.0).
Third-party implementations, base models, tokenizers, and other external dependencies are not relicensed by this repository and remain subject to their respective licenses and terms. Any upstream license or notice files included in this repository continue to apply to the corresponding upstream materials.
4 commits