SD1.5 IP-Adapter Plus Face (GGUF, safetensors)

DreamShaper 7 with the IP-Adapter plus-face adapter and its image encoder, so TokForge can put the person from a reference photo into any scene you describe.

Published by TokForge for on-device inference.


What it is	Image generator (reference photo)
Format	f16 GGUF base for stable-diffusion.cpp, plus IP-Adapter and image encoder safetensors
Runs on	Android phones (stable-diffusion.cpp, CPU or Adreno OpenCL GPU)
Phone class	8 GB RAM or more (TokForge catalog)
Download	4.84 GB (5 files)
Base model	Lykon/dreamshaper-7, h94/IP-Adapter
License	Several: CreativeML OpenRAIL-M plus Lykon's Civitai terms (base), Apache-2.0 (adapter), MIT (image encoder)

TokForge

Website: https://tokforge.ai
Discord: https://discord.gg/Acv3CBtfVm
Google Play: https://play.google.com/store/apps/details?id=dev.tokforge
iOS TestFlight: https://testflight.apple.com/join/jnufjzRr

Runs on-device in the TokForge app.

Use it in TokForge

Install TokForge from Google Play.
On Android, open Models > Recommended > Image and download SD1.5 IP-Adapter (Reference Identity). TokForge lists it on phones with 8 GB RAM or more.
In a chat, attach a clear photo of the person's face as a reference, then describe the scene (for example "me as a superhero flying over New York"). The adapter keeps the face; the prompt drives everything else.
The model runs on the phone; once it is downloaded, making pictures needs no connection.

Collections: TokForge GGUF Models, TokForge Image Models (Android).

Files

File	Size	What it is
`ip-adapter-plus-face_sd15.safetensors`	98.2 MB	IP-Adapter plus-face for SD1.5 (h94/IP-Adapter, Apache-2.0)
`ip_adapter_clip_vision_vith.safetensors`	2.53 GB	OpenCLIP ViT-H-14 image encoder for the reference photo (MIT)
`manifest.json`	1.29 KB	Render defaults, licences, sizes and md5 of the three model files
`sd15-base-f16.gguf`	2.21 GB	DreamShaper 7 base: CLIP text encoder, UNet and VAE in one f16 GGUF
`MD5SUMS`	199 B	md5 of the three model files

manifest.json and MD5SUMS carry the integrity hashes and render defaults.

About the model

The reference-identity image route for the TokForge Android app. Attach a photo of a person, then render that person in any scene. The plus-face IP-Adapter transfers the face only while the prompt drives the whole scene.

This bundle runs on the on-device stable-diffusion.cpp GGUF engine (TokForge's IP-Adapter port) on CPU and Adreno OpenCL. SD1.5 is light enough for any 8 GB+ phone, the broadest-reach identity tier (lighter than the SDXL PhotoMaker and SDXL IP-Adapter tiers).

File	License	Contents
`sd15-base-f16.gguf`	CreativeML-OpenRAIL-M	DreamShaper-7 (SD1.5 realistic finetune), CLIP text encoder + UNet + VAE in one f16 GGUF
`ip-adapter-plus-face_sd15.safetensors`	Apache-2.0	IP-Adapter plus-face (`h94/IP-Adapter`), 16-token Resampler + decoupled cross-attn
`ip_adapter_clip_vision_vith.safetensors`	MIT	OpenCLIP ViT-H-14 image encoder (the plus-face path needs ViT-H, not bigG)

Why this base, and why f16

The base is the standard, non-LCM DreamShaper-7, the same realistic SD1.5 finetune TokForge ships on its other image tiers. It is converted at f16 (full precision) so the IP-Adapter's decoupled cross-attention and the face Resampler keep subject quality high; a q4_0 base weakens the transferred identity.

Why plus-face

The plus-face Resampler extracts the face only (16 tokens from the ViT-H penultimate hidden state), so identity is preserved while the prompt controls the scene. The base ip-adapter_sd15 projects the whole pooled CLIP embedding (4 tokens) and carries the reference's whole scene with it. The TokForge sd.cpp IP-Adapter loader auto-detects plus-face by the presence of image_proj.latents.

Render settings

Setting	Value
sampler	`euler_a`
scheduler	`discrete`
steps	`30` (full quality; fewer = faster)
cfg-scale	`7.0`
ip-adapter-scale	`0.6` (about 0.5 to 0.6 keeps the scene with recognizable identity; about 0.8 reconstructs the reference)
resolution	`512x512` (SD1.5 native)

TokForge runs it through its IP-Adapter port of stable-diffusion.cpp, equivalent to:

sd -M img_gen \
   -m sd15-base-f16.gguf \
   -p "as a superhero flying over New York" \
   -n "<strong negative>" \
   --clip_vision ip_adapter_clip_vision_vith.safetensors \
   --ip-adapter ip-adapter-plus-face_sd15.safetensors \
   --ip-adapter-image <your_face.jpg> \
   --ip-adapter-scale 0.6 \
   --cfg-scale 7.0 --sampling-method euler_a --scheduler discrete \
   --steps 30 -H 512 -W 512

How it was made

Base converted from Lykon/dreamshaper-7 (diffusers) to a single f16 GGUF via the TokForge stable-diffusion.cpp convert path (-M convert --type f16).
Adapter + image encoder copied verbatim from h94/IP-Adapter (models/ip-adapter-plus-face_sd15.safetensors, models/image_encoder/model.safetensors); both files are byte-identical to the upstream ones.

Limitations

The --ip-adapter options belong to TokForge's IP-Adapter port; stock stable-diffusion.cpp builds may not have them.
Plus-face carries the face only, so keep the face visible and unobstructed for a recognizable result.

License

This is an aggregate of three independently-licensed components, and each retains its own license:

DreamShaper-7 base (sd15-base-f16.gguf): CreativeML-OpenRAIL-M (Lykon/dreamshaper-7). Use must comply with the OpenRAIL-M use-based restrictions.
IP-Adapter plus-face (ip-adapter-plus-face_sd15.safetensors): Apache-2.0 (h94/IP-Adapter).
OpenCLIP ViT-H-14 image encoder (ip_adapter_clip_vision_vith.safetensors): MIT (OpenCLIP / LAION ViT-H-14).

The non-commercial IP-Adapter-FaceID / InsightFace path is NOT used here, only the Apache-2.0 base + plus-face adapters from h94/IP-Adapter.

DreamShaper 7 is also under Lykon's Civitai terms: no selling the model or merges of it.

Credits

DreamShaper 7 by Lykon (Civitai, Hugging Face). Used under the CreativeML OpenRAIL-M license and the creator's Civitai terms. Lykon's Civitai terms: no selling the model or merges of it.
Stable Diffusion v1.5 by Runway and CompVis (Hugging Face). Used under the CreativeML OpenRAIL-M license.
IP-Adapter by Tencent AI Lab (h94) (Hugging Face). Used under the Apache-2.0 license.
OpenCLIP ViT-H-14 image encoder by LAION (Hugging Face). Used under the MIT license.
Converted to GGUF with stable-diffusion.cpp by leejet (MIT).