Instructions to use zakria/Project_NLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zakria/Project_NLP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="zakria/Project_NLP")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("zakria/Project_NLP") model = AutoModelForCTC.from_pretrained("zakria/Project_NLP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from zakria/Project_NLP: direct link, hf CLI and curl.
- Browser
- Download file 268 Bytes
-
https://huggingface.co/zakria/Project_NLP/resolve/main/vocab.json
- Command line
-
hf download hf://zakria/Project_NLP/vocab.json
-
curl -L -o vocab.json https://huggingface.co/zakria/Project_NLP/resolve/main/vocab.json
268 Bytes
| {"'": 0, "u": 1, "i": 2, "p": 3, "f": 4, "z": 5, "o": 6, "m": 7, "q": 8, "c": 9, "y": 10, "k": 11, "n": 12, "l": 13, "d": 14, "s": 15, "w": 16, "a": 17, "e": 18, "r": 19, "j": 20, "h": 21, "b": 23, "t": 24, "v": 25, "x": 26, "g": 27, "|": 22, "[UNK]": 28, "[PAD]": 29} |