Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Romanian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use iulik-pisik/all_data_model_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iulik-pisik/all_data_model_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="iulik-pisik/all_data_model_base")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("iulik-pisik/all_data_model_base") model = AutoModelForSpeechSeq2Seq.from_pretrained("iulik-pisik/all_data_model_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d252330162917f237f4bc39a32304f7062aeba674e84b067934c6e5cf700c22
- Size of remote file:
- 5.05 kB
- SHA256:
- 914285e1a0c2e5864b19f6a2fb7d83aab760388d4a52e89441f35245bf9d35cc
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