Instructions to use TDT4310-NLP/nou_classifier_raw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TDT4310-NLP/nou_classifier_raw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TDT4310-NLP/nou_classifier_raw")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TDT4310-NLP/nou_classifier_raw") model = AutoModelForSequenceClassification.from_pretrained("TDT4310-NLP/nou_classifier_raw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from TDT4310-NLP/nou_classifier_raw: direct link, hf CLI and curl.
- Browser
- Download file 2.84 GB
-
https://huggingface.co/TDT4310-NLP/nou_classifier_raw/resolve/main/optimizer.pt
- Command line
-
hf download hf://TDT4310-NLP/nou_classifier_raw/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/TDT4310-NLP/nou_classifier_raw/resolve/main/optimizer.pt
2.84 GB
- Xet hash:
- bc361dbe4694aa4b6c64732fc5c082a05bfa79ce31429b664c4a476cc22d9b95
- Size of remote file:
- 2.84 GB
- SHA256:
- 0fb3009ebd2e4e3b85eea6205b9f8dfed05d43e270fcafb455e6137f4d55a5b9
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