Instructions to use STUDENT-135080/NLP_ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use STUDENT-135080/NLP_ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="STUDENT-135080/NLP_")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("STUDENT-135080/NLP_") model = AutoModelForSequenceClassification.from_pretrained("STUDENT-135080/NLP_") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| language: | |
| - en | |
| tags: | |
| - BERT | |
| - finance | |
| - SENTIMENT-ANALYSIS | |
| - text-classification | |
| - NLP | |