Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Mongolian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use student2008/whisper-tiny-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use student2008/whisper-tiny-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="student2008/whisper-tiny-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("student2008/whisper-tiny-es") model = AutoModelForSpeechSeq2Seq.from_pretrained("student2008/whisper-tiny-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from student2008/whisper-tiny-es: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/student2008/whisper-tiny-es/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://student2008/whisper-tiny-es/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/student2008/whisper-tiny-es/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 2a20dd534a4eea3b946446afc5a466bfe480a90eb8b5d3264985acbd053047b1
- Size of remote file:
- 967 MB
- SHA256:
- ccbde6a228d0f920a6bc061744860d03d4134ea1dbd290ec2e4cf3ad82d7ca80
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