Instructions to use callgg/higgs-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/higgs-decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("callgg/higgs-decoder", 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
Update config.json
Browse files- config.json +3 -1
config.json
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@@ -1,4 +1,5 @@
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{
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"architectures": [
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"HiggsAudioModel"
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],
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"skip_audio_tower": true,
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"text_config": {
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"_attn_implementation_autoset": false,
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"add_cross_attention": false,
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"architectures": [
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"LlamaForCausalLM"
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"use_audio_out_self_attention": 0,
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"use_delay_pattern": true,
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"use_rq_transformer": false
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-
}
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{
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"_name_or_path": "model_initialization/higgs_audio_Llama-3.2-3B_dual_ffn_0_1_code8_size1024_rev",
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"architectures": [
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"HiggsAudioModel"
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],
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"skip_audio_tower": true,
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"text_config": {
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"_attn_implementation_autoset": false,
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"_name_or_path": "/fsx/models/Llama-3.2-3B",
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"add_cross_attention": false,
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"architectures": [
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"LlamaForCausalLM"
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"use_audio_out_self_attention": 0,
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"use_delay_pattern": true,
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"use_rq_transformer": false
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+
}
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