Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use josephhaaga/transcribe-arlco-calls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use josephhaaga/transcribe-arlco-calls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="josephhaaga/transcribe-arlco-calls")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("josephhaaga/transcribe-arlco-calls") model = AutoModelForSpeechSeq2Seq.from_pretrained("josephhaaga/transcribe-arlco-calls") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 018ea84d0d864714981667bd30f16c13699a4257d5a0a57312ba2fe792456b2d
- Size of remote file:
- 5.5 kB
- SHA256:
- e5546bb7f163934519a3415edbfa512b99a59d396fb984860041c0664dbe0bab
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