Instructions to use altbit/avatarsvc-prep-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use altbit/avatarsvc-prep-models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("altbit/avatarsvc-prep-models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
altbit/avatarsvc-prep-models
Unmodified re-publication of two Apache-2.0 models, as sub-folders of one repository, so that one model reference caches both (the avatar service's prep endpoint). No weight, config or tokenizer file has been changed. Each sub-folder is an unmodified copy (or, for a diffusers pipeline, an unmodified SUBSET: the components its model_index.json names) of the upstream commit below.
| Folder | Upstream (repo @ commit) | Files | Licence |
|---|---|---|---|
flux/ |
black-forest-labs/FLUX.1-schnell @ 741f7c3ce8b383c54771c7003378a50191e9efe9 |
23 | Apache-2.0 |
qwen3-tts/ |
Qwen/Qwen3-TTS-12Hz-1.7B-Base @ fd4b254389122332181a7c3db7f27e918eec64e3 |
13 | Apache-2.0 |
Upstream model cards are copied beside this file where the sub-folder does not already carry one (README.<folder>.upstream.md). Full licence: LICENSE.
Files (sha256)
flux/model_index.json536 B24946df21ff25e210486b5f6b14208983a90c9c73f8d48cfa724c0e4e03f7201flux/scheduler/scheduler_config.json274 Bb129cebacf8f851867ec5c7c4d3f4bf787e232525a53becf4df5a72278a788d5flux/text_encoder/config.json613 Bd79d5c8c6ce85112a923d621a5412886ddbbb0636210fc0f72f450582e675542flux/text_encoder/model.safetensors246144352 B893d67a23f4693ed42cdab4cbad7fe3e727cf59609c40da28a46b5470f9ed082flux/text_encoder_2/config.json782 B9001e5a8ae0571a362f806b87b6105dd1a15c33dca237b606d2561164109beebflux/text_encoder_2/model-00001-of-00002.safetensors4994582224 Bec87bffd1923e8b2774a6d240c922a41f6143081d52cf83b8fe39e9d838c893eflux/text_encoder_2/model-00002-of-00002.safetensors4530066360 Ba5640855b301fcdbceddfa90ae8066cd9414aff020552a201a255ecf2059da00flux/text_encoder_2/model.safetensors.index.json19885 B3bacec0f0cf392399d4a385908f67dd73df99c9e9cfee669f148858ba9fbdb0aflux/tokenizer/merges.txt524619 B9fd691f7c8039210e0fced15865466c65820d09b63988b0174bfe25de299051aflux/tokenizer/special_tokens_map.json588 B2cdb3b8331a60c92fc1e55a13e9fd61fd2293c5a51275fdcccd62b780052530eflux/tokenizer/tokenizer_config.json705 B6bdcee9ccce2a16ca2b4c0c5ed00b42c50ea225f4472a8c4c1e963a2902c2881flux/tokenizer/vocab.json1059962 Be089ad92ba36837a0d31433e555c8f45fe601ab5c221d4f607ded32d9f7a4349flux/tokenizer_2/special_tokens_map.json2543 B7a1985a994c41886db38c719d2a3d2f40606663cc19d7c5d6a85d349320e06d2flux/tokenizer_2/spiece.model791656 Bd60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86flux/tokenizer_2/tokenizer.json2424235 Bf5dfec163765e18e270537fe896c49f5fad74db1525641d9b255a3008b999596flux/tokenizer_2/tokenizer_config.json20817 B1a3d2db64215ed77854dd4208aac5f8361c1b5471cabd19c0ef1472d1a895eb0flux/transformer/config.json321 B397cfb92299488013ec3af6142a2a877366f8d2e44efbb4f3e33479e7960d3d0flux/transformer/diffusion_pytorch_model-00001-of-00003.safetensors9962580296 B9b633dbe87316385c5b1c262bd4b5a01e3d955170661d63dcec8a01e89c0d820flux/transformer/diffusion_pytorch_model-00002-of-00003.safetensors9949328904 B58b4434078f0c2567ddc54e3b5cbf39626ab55fbd9d5c22956e183668f535decflux/transformer/diffusion_pytorch_model-00003-of-00003.safetensors3870584832 Be2cbc25471ed5186e69a9b51098300cb2f612556453e38a372c851a220ed238dflux/transformer/diffusion_pytorch_model.safetensors.index.json120822 B783f857a5872f069e75daf4a5abe5efd6ff9ec2f37d71159767910cebfe048a6flux/vae/config.json774 Bbc1e208f414a315365fbecf426838f43b87c9d5c051219e0968a56e2644b2998flux/vae/diffusion_pytorch_model.safetensors167666902 Bf5b59a26851551b67ae1fe58d32e76486e1e812def4696a4bea97f16604d40a3qwen3-tts/.gitattributes1519 B11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361qwen3-tts/README.md57817 B621b7e88f1867bc03d817176fc1f7f55f4b5a70654b2a07fdcda1e169efb024bqwen3-tts/config.json4494 Bb4f01752d15a488abde3e1ab44723ae4f4b9e68a4037257b098b3737893cc1f9qwen3-tts/generation_config.json245 Bf1b90b4513f3b34c62851049e2492d7b4c5940daf1276f89c82b8ef04127f3aaqwen3-tts/merges.txt1671839 B599bab54075088774b1733fde865d5bd747cbcc7a547c5bc12610e874e26f5e3qwen3-tts/model.safetensors3857413744 B38fc7fc51c5e776e840414b6fd443962e9411b9654888fd7913e4da643cb857cqwen3-tts/preprocessor_config.json127 Befdde1022ea9d76928bf7a9cd53139138f5ba2e466e837f08f6105ab1af1c119qwen3-tts/speech_tokenizer/config.json2336 Bee65bb901c876664ab8707c487157aa1a6ee57c65969b28fb5ec9dc211e68167qwen3-tts/speech_tokenizer/configuration.json76 B6bc26d64eb5024b4d1dab5a52371958b429256d6c9d59787f1f5294a54e0cebdqwen3-tts/speech_tokenizer/model.safetensors682293092 B836b7b357f5ea43e889936a3709af68dfe3751881acefe4ecf0dbd30ba571258qwen3-tts/speech_tokenizer/preprocessor_config.json234 Bfcb3805e597e786d4067706e602f6688524640f8d3396790e2e09b5942fcbdfbqwen3-tts/tokenizer_config.json7344 Bdc3c31c3bdaedd5016382bb3cbe07323026775ad51f5a4fb564505992ae4a670qwen3-tts/vocab.json2776833 Bca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910
- Downloads last month
- -
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support