Automatic Speech Recognition
Transformers
PyTorch
Hungarian
wav2vec2
Generated from Trainer
hf-asr-leaderboard
model_for_talk
mozilla-foundation/common_voice_8_0
robust-speech-event
Eval Results (legacy)
Instructions to use Akashpb13/xlsr_hungarian_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akashpb13/xlsr_hungarian_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Akashpb13/xlsr_hungarian_new")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Akashpb13/xlsr_hungarian_new") model = AutoModelForCTC.from_pretrained("Akashpb13/xlsr_hungarian_new") - Notebooks
- Google Colab
- Kaggle
upload model files
Browse files- pytorch_model.bin +1 -1
- vocab.json +1 -1
pytorch_model.bin
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vocab.json
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{"h": 0, "f": 1, "g": 2, "á": 3, "l": 4, "ú": 5, "n": 6, "ű": 7, "u": 8, "y": 9, "ó": 10, "í": 11, "o": 12, "t": 13, "s": 14, "z": 15, "ő": 16, "p": 17, "d": 18, "é": 20, "ö": 21, "i": 22, "-": 23, "b": 24, "x": 25, "k": 26, "ü": 27, "w": 28, "r": 29, "e": 30, "c": 31, "j": 32, "q": 33, "v": 34, "m": 35, "a": 36, "|": 19, "[UNK]": 37, "[PAD]": 38}
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