Instructions to use Masterx/CrisperWhisper2.0-turbo-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Masterx/CrisperWhisper2.0-turbo-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'Masterx/CrisperWhisper2.0-turbo-ONNX');
CrisperWhisper 2.0 Turbo β ONNX
ONNX export of nyralabs/CrisperWhisper2.0_turbo (verbatim, multilingual speech recognition with word-accurate timing), in the onnx-community / Optimum layout:
onnx/encoder_model{_fp16,_q4}.onnxβ mel encoder (input_features [1, 128, T]βlast_hidden_state)onnx/decoder_model_merged{_fp16,_q4}.onnxβ KV-cache merged decoder (use_cache_branch) withcross_attentions.{i}outputs for DTW word timestamps against the model's supervised alignment heads (generation_config.json)
Decoder prompt layout (the model was trained with mode tags before <|startoftranscript|>):
[verbatim_1][verbatim_2][verbatim_3][verbatim_4][verbatim_5] (<htx> hotwords <ehtx>)? <|startoftranscript|> <|lang|> <|transcribe|> <|notimestamps|>
Verbatim output keeps disfluencies as bracketed event tokens ([UM], [UH], [laughter],
[cough], ...). Intended mode uses [intended_1..5] tags instead. See the
upstream model card and
nyrahealth/CrisperWhisper for details.
License β READ BEFORE USE
These weights are a Derivative Work of nyralabs/CrisperWhisper2.0_turbo and are
distributed under the Nyra Health Non-Commercial Research License (see LICENSE.md
in this repository β identical to the upstream license). In short:
- Non-commercial / research use only. No production or operational deployment, and no use from which commercial gain is derived.
- Share-alike. Any further derivative must remain under this same license and may not be re-released under a permissive or commercial license.
- By downloading or using these files you agree to be bound by the terms of
LICENSE.md. - Commercial licensing: contact licensing@nyra-labs.com.
Conversion: Optimum main_export (task automatic-speech-recognition-with-past,
output_attentions=True), fp16 via onnxconverter-common (keep_io_types=True),
q4 via onnxruntime MatMulNBitsQuantizer(bits=4, block_size=32, is_symmetric=True).
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Base model
nyralabs/CrisperWhisper2.0_turbo