Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_small_beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_small_beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_small_beta")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_small_beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_small_beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_state.bin from NbAiLabArchive/scream_small_beta: direct link, hf CLI and curl.
- Browser
- Download file 10.9 kB
-
https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/d13ecb40aa996b3985fb8d2d8327b0d7bb843f7e/training_state.bin
- Command line
-
hf download hf://NbAiLabArchive/scream_small_beta@d13ecb40aa996b3985fb8d2d8327b0d7bb843f7e/training_state.bin
-
curl -L -o training_state.bin https://huggingface.co/NbAiLabArchive/scream_small_beta/resolve/d13ecb40aa996b3985fb8d2d8327b0d7bb843f7e/training_state.bin
10.9 kB
- Xet hash:
- e43f34c7aaeb803568cacd2b8bc55d86c473220c71dbfa3f5d85182d0d14883e
- Size of remote file:
- 10.9 kB
- SHA256:
- b9a5607e6733995006a8755fc845d3731e8689a287305b365edf37d8aee7258e
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