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:
- b36eb11822fb51e281ea782e78c1b1816050dac8c0f114e06622fd86cae55d2e
- Size of remote file:
- 5.3 kB
- SHA256:
- 36f5dca2e90a9e1c7683a3a1f333be1f1e80b5afe3d954c7902a548359b3e1af
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.