Slides: Optimizing inference for voice models in production - Philip Kiely, Baseten
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Optimizing inference for voice models in production - Philip Kiely, Baseten
Relationship To World's Fair 2026
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Extracted Slides

OCR text:
INNOVATIONPARTNER
aws
PLATINUMSPONSORS
Graphite
WWindsurf
MongoDB
daily
augment code
Workos

OCR text:
Hi, I'm Philip from Baseten 7
« Developer relations at Baseten a te a a ° — . :
+ Based in SFBA @@@ ai a a 2a
* Favorite voice model: Orpheus TTS 4 ia | : »
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a Microsoft OCU

OCR text:
Agenda |
1. TTS model architecture
2. TTS performance metrics
3. Orpheus TTS optimization techniques
4. Orpheus TTS performance benchmarks
5. Infrastructure and client code
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u Microsoft § ou?
, os

OCR text:
"archttectures':[
AIE CanopyLabs OrpheusTTS Example: ·Extendedcontextlength Increasedvocabsizefor Llama3.23Bbackbone speech-specifictokens withRoPEscaling "inittalizer_range:.82. "attention_btas:false, "attentton_dropout:B., "bos_token_ld:128808, "head_din':128, "htdden_act":"stlu', "htdden_s(ze²:3872, "ax_posttton_embeddings:131872, "nu_attentton_heads*:24, "nun_htdden_layers”:28, "num_key_value_heads':8, "eos_token_(d:12801, internediate_stze:8192, "pretraining_tp":1, uesado ee11.ad11apo res_norn_eps:le- "factor':32.6, "low_freq_factor'x1.6,.oe11.:odado "high_freq_factor':4.0. suppqauoasodxee5o
"tle_word_erbeddings':true.o "transformers_verston:4.47.0 "rope_theta':58e889.8.
vocab_stze:156939
Microsoft smol?

OCR text:
AIE settings engine TensorRT-LLM ·Post-training quantization toFP8 ·QuantizeKVcache OptimizeforHopperarchitecture build: runtlee: ensor_oarallelcount:1 plugin_conftguratton: Ay.cache_free.opu.#e.fraction:985 base model:llama Quantization_type:fpB_kv enable_chunked_context:true nax_batch_slze:256 max_mum_tokens:16384 checkpoint repo:baseten/orpheus-3b-e.1-ft caltb.dataset:"cnn_datlyaatl" reviston:b9eb57... use_fpecontext_foho:true
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Microsoft smol?

OCR text:
AI Engineer
World's Fair
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