Instructions to use Blaise-MR/pytorch_sentiment_textnotes1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Blaise-MR/pytorch_sentiment_textnotes1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Blaise-MR/pytorch_sentiment_textnotes1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Blaise-MR/pytorch_sentiment_textnotes1") model = AutoModelForSequenceClassification.from_pretrained("Blaise-MR/pytorch_sentiment_textnotes1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- model.safetensors +1 -1
model.safetensors
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