Instructions to use nruigrok/TK2025_talkshows with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nruigrok/TK2025_talkshows with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nruigrok/TK2025_talkshows")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nruigrok/TK2025_talkshows") model = AutoModelForSequenceClassification.from_pretrained("nruigrok/TK2025_talkshows", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72039ea5f7d40053ddb5f8c61ffd4bbe4d69b35a3289a9cdd4768ae99378484b
- Size of remote file:
- 17.1 MB
- SHA256:
- 33cd99e33ce09bdd8a6136fddfe90a1c47f85bafedf7309d0eecc19012d43586
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