Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Italian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use FCameCode/whisper-tiny-it-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FCameCode/whisper-tiny-it-8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="FCameCode/whisper-tiny-it-8")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("FCameCode/whisper-tiny-it-8") model = AutoModelForSpeechSeq2Seq.from_pretrained("FCameCode/whisper-tiny-it-8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
c2ca7f9 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:1561e7f1ff96c49d403d344fed719070b0402e0c77040a6270333096bf5388e4
size 3515
|