Text Classification
Transformers
PyTorch
Safetensors
English
bert
classification
text-embeddings-inference
Instructions to use morenolq/spotify-podcast-advertising-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morenolq/spotify-podcast-advertising-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="morenolq/spotify-podcast-advertising-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("morenolq/spotify-podcast-advertising-classification") model = AutoModelForSequenceClassification.from_pretrained("morenolq/spotify-podcast-advertising-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from morenolq/spotify-podcast-advertising-classification: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/morenolq/spotify-podcast-advertising-classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://morenolq/spotify-podcast-advertising-classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/morenolq/spotify-podcast-advertising-classification/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 9dd2293b4414deddb3254a476f0b0dcaeaf94420bf82bd6f4656e1f9da0c3fc9
- Size of remote file:
- 433 MB
- SHA256:
- 206c74d80727276c4dc04bbc28ddf1722b59fa28fc1d1a237f93af18666f1cb8
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