Instructions to use ChunLok/CAM_sentiment_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChunLok/CAM_sentiment_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ChunLok/CAM_sentiment_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ChunLok/CAM_sentiment_model") model = AutoModelForSequenceClassification.from_pretrained("ChunLok/CAM_sentiment_model") - Notebooks
- Google Colab
- Kaggle
CAM_sentiment_model
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Model description
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Intended uses & limitations
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Training hyperparameters
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Training results
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Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for ChunLok/CAM_sentiment_model
Base model
yiyanghkust/finbert-pretrain