Instructions to use Blaise-MR/pytorch_sentiment_textnotes3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Blaise-MR/pytorch_sentiment_textnotes3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Blaise-MR/pytorch_sentiment_textnotes3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Blaise-MR/pytorch_sentiment_textnotes3") model = AutoModelForSequenceClassification.from_pretrained("Blaise-MR/pytorch_sentiment_textnotes3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload tokenizer
Verified signature54138c1 -
Upload BertForSequenceClassification
Verified signature6564c0a -
Upload tokenizer
Verified signature480e57d -
Upload BertForSequenceClassification
Verified signatureefe7e29 -
initial commit
Verified signature0075baf