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 optimizer.pt from Pclanglais/transcript-text-analysis: direct link, hf CLI and curl.
- Browser
- Download file 2.23 GB
-
https://huggingface.co/Pclanglais/transcript-text-analysis/resolve/main/optimizer.pt
- Command line
-
hf download hf://Pclanglais/transcript-text-analysis/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Pclanglais/transcript-text-analysis/resolve/main/optimizer.pt
2.23 GB
- Xet hash:
- 75806de5098946e82d4656235c48ffc68a002d5fe05af7b248626602380563eb
- Size of remote file:
- 2.23 GB
- SHA256:
- 9fd917d9135af97af2e6beb9601a7271692252feb68f771cf700fc43e479eaa5
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