Instructions to use gciaffoni/modelLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gciaffoni/modelLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="gciaffoni/modelLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("gciaffoni/modelLM") model = AutoModelForCTC.from_pretrained("gciaffoni/modelLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download alphabet.json from gciaffoni/modelLM: direct link, hf CLI and curl.
- Browser
- Download file 298 Bytes
-
https://huggingface.co/gciaffoni/modelLM/resolve/main/alphabet.json
- Command line
-
hf download hf://gciaffoni/modelLM/alphabet.json
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curl -L -o alphabet.json https://huggingface.co/gciaffoni/modelLM/resolve/main/alphabet.json
298 Bytes
| {"labels": [" ", "'", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z", "\u00e0", "\u00e1", "\u00e8", "\u00e9", "\u00ec", "\u00ed", "\u00f2", "\u00f3", "\u00f9", "\u00fa", "\u2047", "", "<s>", "</s>"], "is_bpe": false} |