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
transcribe-arlco-calls / runs /Feb09_21-28-59_9f56bd31de57 /events.out.tfevents.1739136542.9f56bd31de57.1675.0
- Xet hash:
- 2c4fae16260d89a1482af177ec6e3eb127b0ccce480a02a66083beb8980072e8
- Size of remote file:
- 24.6 kB
- SHA256:
- 6ce8dd7f158e70f5414b10aaf71f6cd0c86750129c19443da96f546241c2668a
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