ONNX

[we11as22]

How can I launch GigaAM_RNNT using ONNX?
sherpa-onnx crashes colab(
Please, help me with this

[csukuangfj]

sherpa-onnx crashes colab(

Could you be more specific?

[we11as22]

Export ONNX model

onnx_enc_model_fname = onnx_model_path + "/" + 'encoder.onnx'
onnx_dec_model_fname = onnx_model_path + "/" + 'decoder.onnx'
onnx_joint_model_fname = onnx_model_path + "/" + 'joint.onnx'

model.encoder.export(onnx_enc_model_fname)
model.decoder.export(onnx_dec_model_fname)
model.joint.export(onnx_joint_model_fname)

model_file = "/content/tokenizer_all_sets/tokenizer.model"

vocab_file = "/content/tokenizer.vocab"#model_file.replace(".model", ".vocab")

sp = spm.SentencePieceProcessor()
sp.Load(model_file)
vocabs = [sp.IdToPiece(id) for id in range(sp.GetPieceSize())]
with open(vocab_file, "w") as vfile:
for v in vocabs:
id = sp.PieceToId(v)
vfile.write(f"{v}\t{sp.GetScore(id)}\n")
print(f"Vocabulary file is written to {vocab_file}")

encoder = onnx_enc_model_fname
decoder = onnx_dec_model_fname
joiner = onnx_joint_model_fname
tokens = "/content/tokenizer_all_sets/vocab.txt"
bpe_vocab="/content/tokenizer_all_sets/tokenizer.vocab"

recognizer = sherpa_onnx.OfflineRecognizer.from_transducer(
encoder=encoder,
decoder=decoder,
joiner=joiner,
tokens=tokens,
bpe_vocab=bpe_vocab,
feature_dim=64,
num_threads=1,
provider="cpu",
sample_rate=16000,
debug=True
)

*colab is dead

[csukuangfj]

I suggest that you learn how to ask a question so that others can help you.

[csukuangfj]

@we11as22
Please see
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-ctc/nemo/russian.html

We have supported it in sherpa-onnx