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decibel-hq
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Model Details
Model Provider
decibel-hq
Model Tree
canopylabs/orpheus-3b-0.1-ft
Input Modalities
Output Modalities
Supported Functionality
laugh
sigh
price
phone
ask
short
long
convo
whisper
chuckle
Prompt format: reso: <your text> with inline paralinguistic tags:
<laugh> <chuckle> <sigh> <gasp> <whisper> <pause>
python
import torchfrom transformers import AutoModelForCausalLM, AutoTokenizerfrom peft import PeftModelbase = AutoModelForCausalLM.from_pretrained("canopylabs/orpheus-3b-0.1-ft", torch_dtype=torch.bfloat16, device_map="auto")model = PeftModel.from_pretrained(base, "decibel-hq/reso1-3b-en")tokenizer = AutoTokenizer.from_pretrained("decibel-hq/reso1-3b-en")# sequence format + SNAC decode: 7 audio tokens/frame from id 128266,# wrapped in [128259] text [128009,128260,128261,128257] audio [128258,128262]
Sampling: temperature 0.6, top_p 0.95, repetition_penalty >= 1.1 (required —
lower values cause audio loops). Streaming: decode SNAC frames incrementally
(7 tokens = ~85 ms audio); a GGUF build for llama.cpp is at
decibel-hq/reso1-3b-en-GGUF.
<whisper>/<pause> are corpus-taught rather than base-native — less robustDecibel Labs — Reso voice models (2026). https://github.com/decibel-hq/reso