Instructions to use aekupor/eliciting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aekupor/eliciting with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aekupor/eliciting")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aekupor/eliciting") model = AutoModelForSequenceClassification.from_pretrained("aekupor/eliciting", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Remove formatting code (moved to talk_move_handler)
e711d6b -
Test remove call function
Ashlee Kupor2a6910f
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Split up long utterances
Ashlee Kupor1690680 -
Update handler to take in and process vtt file
Ashlee Kupora2b60e7
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make handler and test for it
Ashlee Kupora8d332e