Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use Eimhin03/ModelsMCV22Training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eimhin03/ModelsMCV22Training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Eimhin03/ModelsMCV22Training")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Eimhin03/ModelsMCV22Training") model = AutoModelForSpeechSeq2Seq.from_pretrained("Eimhin03/ModelsMCV22Training", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Eimhin03/ModelsMCV22Training: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/Eimhin03/ModelsMCV22Training/resolve/main/training_args.bin
- Command line
-
hf download hf://Eimhin03/ModelsMCV22Training/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Eimhin03/ModelsMCV22Training/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- 92b7a9a1d09c0eabd80c78b6cdc9a796028bd1d909244be27f465b8d3de3a921
- Size of remote file:
- 5.27 kB
- SHA256:
- 3f6512c6eb95056914c699d0c26a3845860e6b48c630d31cce94d1ce92b66e34
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