Instructions to use enactic/avista-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enactic/avista-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enactic/avista-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("enactic/avista-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from enactic/avista-base: direct link, hf CLI and curl.
- Browser
- Download file 127 Bytes
-
https://huggingface.co/enactic/avista-base/resolve/refs%2Fpr%2F1/processor_config.json
- Command line
-
hf download hf://enactic/avista-base@refs/pr/1/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/enactic/avista-base/resolve/refs%2Fpr%2F1/processor_config.json
127 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_avhubert.AVHubertProcessor" | |
| }, | |
| "processor_class": "AVHubertProcessor" | |
| } | |