Instructions to use Priyanship/eval_cache_hindi_only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Priyanship/eval_cache_hindi_only with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Priyanship/eval_cache_hindi_only")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Priyanship/eval_cache_hindi_only") model = AutoModelForCTC.from_pretrained("Priyanship/eval_cache_hindi_only", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 284 Bytes
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"eval_cer": 0.33544957921157537,
"eval_loss": 2.218759059906006,
"eval_model_preparation_time": 0.0044,
"eval_runtime": 43.1274,
"eval_samples": 572,
"eval_samples_per_second": 13.263,
"eval_steps_per_second": 0.835,
"eval_wer": 0.47242942811174493
} |