Instructions to use nlp-chula/traffy-problem-predict with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlp-chula/traffy-problem-predict with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlp-chula/traffy-problem-predict")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlp-chula/traffy-problem-predict") model = AutoModelForSequenceClassification.from_pretrained("nlp-chula/traffy-problem-predict", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b6e69582eec1357adf8b98198958540eb746ac3cfbf180c603f15d899d97e9c
- Size of remote file:
- 17.3 MB
- SHA256:
- 6d0ddf722adac420a806df4a078fa6b5dcf20a10382f9ca1e1127011328ce3a7
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