Chatterbox-Nano is the small sibling of Chatterbox-Turbo: the same AR text-to-speech pipeline with a
GPT2-small T3 backbone (12 layers, 768 hidden, 12 heads)
instead of Turbo's GPT2-medium (24L, 1024D). Upstream's
s3gen_meanflow.safetensors
,
ve.safetensors
and
conds.pt
are
byte-identical
to
ResembleAI/chatterbox-turbo
(same LFS blobs), so this repo ships only the T3 —
use the S3Gen from
cstr/chatterbox-turbo-GGUF
as the companion.
CrispASR's registry does this automatically. Distributed under
MIT license
.
Files
File
Size
Notes
chatterbox-nano-t3-f16.gguf
476 MB
T3 GPT-2 AR model (12L, 768D) + VE + baked conds
chatterbox-nano-t3-q8_0.gguf
345 MB
Quantized T3, recommended deployment default
chatterbox-nano-t3-q4_k.gguf
283 MB
Smaller T3 quant for memory-constrained use
The GGUF carries
chatterbox.t3.n_kv_heads = 12
explicitly (GPT-2 is MHA; CrispASR's built-in default of 16 fits Turbo only). Token ids match upstream inference (
T3Config
: start_text 255, stop_text 0, speech 6561/6562) — the
stop_text_token: 50256
in
t3_nano_v1.yaml
is a training-time artifact that upstream
generate()
never reads.
Usage
# auto-download T3 + Turbo S3Gen companion
crispasr --backend chatterbox-nano -m auto --auto-download \
--tts "Hello from Chatterbox Nano." --tts-output nano.wav
# explicit files
crispasr --backend chatterbox-nano -m chatterbox-nano-t3-q8_0.gguf \
--codec-model chatterbox-turbo-s3gen-q8_0.gguf \
--tts "Hello from Chatterbox Nano." --tts-output nano.wav
Voice cloning (
--voice reference.wav
), the 19
[emotion]
style tokens, and the sampler defaults are identical to the Turbo backend; CFG/min_p/exaggeration are not supported by the Turbo/Nano pipeline (upstream disables them).
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