Instructions to use MENG21/stud-fac-eval-NAIVEBAYES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MENG21/stud-fac-eval-NAIVEBAYES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MENG21/stud-fac-eval-NAIVEBAYES")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MENG21/stud-fac-eval-NAIVEBAYES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.pkl from MENG21/stud-fac-eval-NAIVEBAYES: direct link, hf CLI and curl.
- Browser
- Download file 30.8 kB
-
https://huggingface.co/MENG21/stud-fac-eval-NAIVEBAYES/resolve/main/model.pkl
- Command line
-
hf download hf://MENG21/stud-fac-eval-NAIVEBAYES/model.pkl
-
curl -L -o model.pkl https://huggingface.co/MENG21/stud-fac-eval-NAIVEBAYES/resolve/main/model.pkl
30.8 kB
- Xet hash:
- 874d2e64c7b873a30439abf36a030e7a8c3a5873bf3cf281f48aa6c89d853985
- Size of remote file:
- 30.8 kB
- SHA256:
- 65fd8cd905d5103de4d7734e11d77ab89bb036d9c02e6f9ece5cc4a6bee6b093
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