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unsloth/flux-text-encoders
flux-text-encoders is a machine learning model from unsloth. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusion-single-file. The card lists the license as other.
The two text-encoder files FLUX.1 needs to run under stable-diffusion.cpp, mirrored from comfyanonymous/fluxtextencoders.
Downloads · 30 days
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.safetensors10 GB · 100%
From the Hugging Face model README
The two text-encoder files FLUX.1 needs to run under stable-diffusion.cpp, mirrored from comfyanonymous/flux_text_encoders.
Unsloth Studio fetches these on the no-GPU (native sd.cpp) path. It used to fetch them straight from the community repack; nobody there owes anyone availability, and a rename or a takedown turns every CPU FLUX.1 load into a 404. So they are mirrored here. The weights are unmodified: byte for byte the files of the same name in the source repo.
| File | Size | Upstream model | Licence |
|---|---|---|---|
clip_l.safetensors | 0.23 GiB | openai/clip-vit-large-patch14 (text tower) | MIT |
t5xxl_fp16.safetensors | 9.11 GiB | google/t5-v1_1-xxl (fp16) | Apache-2.0 |
Only these two files are mirrored. The source repo also ships fp8 T5 variants; Studio does not use them, so they are not here.
Two licences, one per file, both reproduced in full in
LICENSE, with the
attribution in NOTICE.
Both permit redistribution.
One caveat worth stating rather than glossing: openai/clip-vit-large-patch14 carries no
licence declaration at all. The MIT terms here are the ones OpenAI attached to
github.com/openai/CLIP, the repository that published those
weights. The source repack labels both its files apache-2.0, which is not right for CLIP-L, so
this mirror splits the two rather than repeating that.
Nothing here is an official OpenAI, Google or ComfyUI product, and nothing here is endorsed by them.