Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
Generated from Trainer
Instructions to use Rolv-Arild/xls-r-300m-npsc-seq2seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rolv-Arild/xls-r-300m-npsc-seq2seq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Rolv-Arild/xls-r-300m-npsc-seq2seq")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("Rolv-Arild/xls-r-300m-npsc-seq2seq") model = AutoModelForSpeechSeq2Seq.from_pretrained("Rolv-Arild/xls-r-300m-npsc-seq2seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Rolv-Arild/xls-r-300m-npsc-seq2seq: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/Rolv-Arild/xls-r-300m-npsc-seq2seq/resolve/main/training_args.bin
- Command line
-
hf download hf://Rolv-Arild/xls-r-300m-npsc-seq2seq/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Rolv-Arild/xls-r-300m-npsc-seq2seq/resolve/main/training_args.bin
3.12 kB
- Xet hash:
- 7c552b7a5f0350e09ac5cc8aaff2f8f6e27228976ae596ae84c6788915cbbe6e
- Size of remote file:
- 3.12 kB
- SHA256:
- 2504c14e486f907f21299d32d6b70636d29c7158530a07ff6a788b8d2edee349
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