Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use kmontg/csml_word2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmontg/csml_word2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kmontg/csml_word2vec")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("kmontg/csml_word2vec") model = AutoModelForCTC.from_pretrained("kmontg/csml_word2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kmontg/csml_word2vec: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/kmontg/csml_word2vec/resolve/main/training_args.bin
- Command line
-
hf download hf://kmontg/csml_word2vec/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kmontg/csml_word2vec/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- b9f8e13708c3adae0a79339d36b93c5c36d1a508d7f74291f324b5d93f38592d
- Size of remote file:
- 5.84 kB
- SHA256:
- aee04aa2155a059adfac2d3714d16d48ebc1acbd1b55eb07890943e28ddec812
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