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 rng_state.pth from Pclanglais/transcript-text-analysis: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/Pclanglais/transcript-text-analysis/resolve/main/rng_state.pth
- Command line
-
hf download hf://Pclanglais/transcript-text-analysis/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Pclanglais/transcript-text-analysis/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- 6e1e5ccd2ae6509687a0f40fa1708b4324a41bde15482e17c49da6d045942720
- Size of remote file:
- 14.2 kB
- SHA256:
- 0e2b27a523a9fd069d1154bb25df70d3244a9c0a81e1eff87a5bf621d7350745
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