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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pclanglais/transcript-text-analysis") model = AutoModelForSequenceClassification.from_pretrained("Pclanglais/transcript-text-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Pclanglais/transcript-text-analysis: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/Pclanglais/transcript-text-analysis/resolve/main/training_args.bin
- Command line
-
hf download hf://Pclanglais/transcript-text-analysis/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Pclanglais/transcript-text-analysis/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- 6b278cfc70d4c771e01b5fd5544d8a9dee202a9389c8587c079bbdd166c54570
- Size of remote file:
- 4.79 kB
- SHA256:
- 458c8d3b21adc6abf439f3039446992fc81ee61cc98a20d37234ca69deb52872
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