Instructions to use nfhakim/sentiment-analysis-c2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nfhakim/sentiment-analysis-c2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nfhakim/sentiment-analysis-c2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nfhakim/sentiment-analysis-c2") model = AutoModel.from_pretrained("nfhakim/sentiment-analysis-c2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7653241d4239eb891dfedcb4e12960d08a570cb9a066b3be064157403007d75a
- Size of remote file:
- 498 MB
- SHA256:
- 37480d527eff36528a50f41a82baca9675d9fba661333cc305fb57fe60263d57
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