Instructions to use obadx/muaalem-model-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use obadx/muaalem-model-v3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import Wav2Vec2BertForMultilevelCTC model = Wav2Vec2BertForMultilevelCTC.from_pretrained("obadx/muaalem-model-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_results.json from obadx/muaalem-model-v3: direct link, hf CLI and curl.
- Browser
- Download file 764 Bytes
-
https://huggingface.co/obadx/muaalem-model-v3/resolve/main/test_results.json
- Command line
-
hf download hf://obadx/muaalem-model-v3/test_results.json
-
curl -L -o test_results.json https://huggingface.co/obadx/muaalem-model-v3/resolve/main/test_results.json
764 Bytes
| { | |
| "test__loss": 0.013308743946254253, | |
| "test__per_phonemes": 0.0044895156070259325, | |
| "test__per_hams_or_jahr": 0.0017701996685671856, | |
| "test__per_shidda_or_rakhawa": 0.0031463302837919397, | |
| "test__per_tafkheem_or_taqeeq": 0.002991813733928723, | |
| "test__per_itbaq": 0.0012993908522054385, | |
| "test__per_safeer": 0.0015150918077191905, | |
| "test__per_qalqla": 0.0012278362083090496, | |
| "test__per_tikraar": 0.00436068518238138, | |
| "test__per_tafashie": 0.0018137546691997701, | |
| "test__per_istitala": 0.0012205770415369523, | |
| "test__per_ghonna": 0.0018531615745340133, | |
| "test__average_per": 0.002335305148109052, | |
| "test__runtime": 563.8142, | |
| "test__samples_per_second": 59.653, | |
| "test__steps_per_second": 0.933, | |
| "epoch": 1.0 | |
| } |