Instructions to use Pclanglais/transcript-text-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pclanglais/transcript-text-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pclanglais/transcript-text-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pclanglais/transcript-text-analysis") model = AutoModelForSequenceClassification.from_pretrained("Pclanglais/transcript-text-analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a406e6640559164cf3d52d81f90e03919dfca1fd3b9f5b6d5764a289aab07de
- Size of remote file:
- 1.12 GB
- SHA256:
- c062326a3d397e2afad75b264aaef47a0923a24c2b66e3d7c43b69b6cc54ed46
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