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