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ChrisColeTech/sdxl
sdxl is a text-to-image model from ChrisColeTech. Use it when you need an image from a text prompt. The card lists the license as unknown.
Full single-file SDXL checkpoints, ready to load as-is.
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Updated Jul 19, 2026
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From the Hugging Face model README
Full single-file SDXL checkpoints, ready to load as-is.
What this repo is: two complete single-file SDXL checkpoints plus the shared tokenizers — weights only, not a retrain. The recommended settings below are the values these weights are actually run with day to day, not copied from the upstream card.
<table> <tr><td><img src="https://huggingface.co/ChrisColeTech/sdxl/resolve/main/samples/apple.png" width="380" alt="prompt: a red apple on a rustic wooden table beside a window, soft daylight, visible wood grain, studio photograph, sharp focus — 1024×1024, 35 steps, guidance 7.5, seed 7"></td><td><img src="https://huggingface.co/ChrisColeTech/sdxl/resolve/main/samples/portrait.png" width="380" alt="prompt: portrait of an older fisherman with a weathered face, natural window light, shallow depth of field, photorealistic — 1024×1024, 35 steps, guidance 7.5, seed 99"></td></tr> <tr><td><sub>**prompt:** `a red apple on a rustic wooden table beside a window, soft daylight, visible wood grain, studio photograph, sharp focus` — 1024×1024, 35 steps, guidance 7.5, seed 7</sub></td><td><sub>**prompt:** `portrait of an older fisherman with a weathered face, natural window light, shallow depth of field, photorealistic` — 1024×1024, 35 steps, guidance 7.5, seed 99</sub></td></tr> <tr><td><img src="https://huggingface.co/ChrisColeTech/sdxl/resolve/main/samples/street.png" width="380" alt="prompt: a rain-slicked Tokyo street at night, neon signs reflecting in puddles, cinematic, 35mm photograph — 1024×1024, 35 steps, guidance 7.5, seed 1234"></td><td><img src="https://huggingface.co/ChrisColeTech/sdxl/resolve/main/samples/anime-girl.png" width="380" alt="Illustrious Anime v4 — anime illustration of a girl in a school uniform standing on a rooftop at sunset, detailed cel shading, clean linework — 1024×1024, 35 steps, guidance 7.5, seed 21"></td></tr> <tr><td><sub>**prompt:** `a rain-slicked Tokyo street at night, neon signs reflecting in puddles, cinematic, 35mm photograph` — 1024×1024, 35 steps, guidance 7.5, seed 1234</sub></td><td><sub>**Illustrious Anime v4** — `anime illustration of a girl in a school uniform standing on a rooftop at sunset, detailed cel shading, clean linework` — 1024×1024, 35 steps, guidance 7.5, seed 21</sub></td></tr> <tr><td><img src="https://huggingface.co/ChrisColeTech/sdxl/resolve/main/samples/anime-city.png" width="380" alt="Illustrious Anime v4 — anime background art of a quiet japanese street in summer, blue sky, detailed clouds, vibrant colors — 1024×1024, 35 steps, guidance 7.5, seed 22"></td><td></td></tr> <tr><td><sub>**Illustrious Anime v4** — `anime background art of a quiet japanese street in summer, blue sky, detailed clouds, vibrant colors` — 1024×1024, 35 steps, guidance 7.5, seed 22</sub></td><td></td></tr> </table>All samples below add this negative prompt, which is not part of the preset in the settings table:
washed out, low contrast, hazy, faded, pastel, bloom, overexposed, glare, milky, foggy, flat lighting, blown highlights, colour castEverything else — resolution, steps, guidance, seed — is exactly the documented preset. Without it these checkpoints, Illustrious especially, render with a heavy pastel bloom; see the note on it below.
Both checkpoints do img2img as well as txt2img. Two sources, each through both checkpoints.
SDXL has no instruction-following training. The prompt is a description of the image to produce, not a command applied to the source:
✅
a still life oil painting of a red apple on a rustic wooden table beside a sunlit window…❌
the same scene rendered as a vivid oil painting…
The instruction form is taken literally. Asking for "the same scene rendered as an
oil painting" returned an apple coated in dripping paint with a paintbrush in frame,
and at higher strength a different scene altogether — at the same strength 0.75
that produced the top row here.
Both keep the subject at 0.75 — same apple, position, scale and light. Juggernaut is heavier impasto and warmer; Illustrious is cleaner and brighter (retaining ~93% of source luminance against Juggernaut's ~85%), rendering more as illustration.
strength and the swept rangeSwept 15–40 steps and guidance 5.0–12.5 at strength 0.75, output was stable
throughout. Below ~0.3 gives little more than a gloss pass; above ~0.85 the source
becomes a loose suggestion.
Bottom row: Juggernaut 1.00× source luminance, Illustrious 1.03×. Juggernaut
applies vertical brushwork to the gradient; Illustrious leaves it close to the
source. In both, the flat circle is reproduced flat — a uniform region carries no
detail for the sampler at strength 0.75, while the graduated area does. Two
consequences for testing: subject loss cannot be observed against a subjectless
source (strength 0.90 passes here and does not preserve a photograph's subject),
and histogram_correlation measures 0.001/−0.017 here against 0.73–0.78 for the
same runs on a photograph.
Values this build is run with in practice. They are read out of a live config when this card is generated, so they cannot drift from what is actually used.
| Parameter | Production value | Meaning |
|---|---|---|
width | 1024 | Output width in pixels |
height | 1024 | Output height in pixels |
steps | 35 | Denoising steps |
guidance | 7.5 | Guidance scale |
preview_every | 5 | Emit a TAESD preview every N steps |
strength | 0.75 | img2img denoise strength (1.0 = ignore the input image) |
Supported modes: txt2img, img2img
.safetensors here is a complete single-file checkpoint..safetensors here is complete on its own; load whichever you want. They share the tokenizers under config/.washed out, hazy, pastel, bloom, …) removes it cleanly — on the anime street it moved tonal spread 164 → 208 and dropped mean brightness 161 → 142. Raising guidance also increases contrast but amplifies everything, including the magenta cast, so the negative prompt is the better lever. On the photographic Juggernaut renders the same negative mostly raises colour saturation (apple 70 → 118) rather than removing haze, so judge it per checkpoint rather than applying it blindly.juggernaut_XL_v9 tolerated it and rendered normally; illustrious_Anime_v4 did not, producing pure noise and near-blank canvases (pixel std as low as 4.1) on every attempt. Fixed 2026-07-18; both checkpoints now render correctly at the settings above, and every sample on this card is a post-fix render.Each .safetensors under combined/ is a complete SDXL checkpoint — unet, both text encoders and the VAE in one file — so any standard SDXL loader can take it directly. The shared CLIP-L and OpenCLIP-G tokenizers live under config/tokenizer/ and config/tokenizer_2/. There is no per-component split here.
If you load these outside the sidecar, set the OpenCLIP-G text encoder's activation to standard GELU. QuickGELU is the right default for CLIP-L only, and getting it wrong yields noise rather than an error — see the notes above.
| File | Size | Role |
|---|---|---|
combined/juggernaut_XL_v9.safetensors | 6.62 GB | full single-file SDXL checkpoint |
combined/illustrious_Anime_v4.safetensors | 6.53 GB | full single-file SDXL checkpoint |
config/tokenizer/tokenizer.json | 3.47 MB | tokenizer / processor |
config/tokenizer_2/tokenizer.json | 3.47 MB | tokenizer / processor |
config/tokenizer/vocab.json | 1.01 MB | tokenizer / processor |
config/tokenizer_2/vocab.json | 1.01 MB | tokenizer / processor |
config/tokenizer/merges.txt | 512.32 KB | tokenizer / processor |
config/tokenizer_2/merges.txt | 512.32 KB | tokenizer / processor |
config/tokenizer/tokenizer_config.json | 737 B | tokenizer / processor |
config/tokenizer_2/tokenizer_config.json | 725 B | tokenizer / processor |
config/model_index.json | 609 B | config |
config/tokenizer/special_tokens_map.json | 472 B | tokenizer / processor |
config/tokenizer_2/special_tokens_map.json | 460 B | tokenizer / processor |
stabilityai/stable-diffusion-xl-base-1.0 (upstream license: openrail++)unknown in this repo's metadata. Refer to the upstream model's license for redistribution and commercial-use terms — several of these bases are non-commercial.