Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Sharpaxis/Sentiment_tweets_distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/Sentiment_tweets_distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/Sentiment_tweets_distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/Sentiment_tweets_distilbert") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/Sentiment_tweets_distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0421c558ebb3b75c29674b64638767a31493297b9562f0776bf71b89a4d22a8e
- Size of remote file:
- 268 MB
- SHA256:
- feb662252fb9e2ae73b05b91e82f74c06c24c44698446aea4317af721feace57
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.