Instructions to use tweettemposhift/topic-topic_random3_seed2-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random3_seed2-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random3_seed2-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random3_seed2-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random3_seed2-bernice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f853e7cc1c8b0a2b5ace9d388f528626d114345cccc736050e900dd82d09abbd
- Size of remote file:
- 1.11 GB
- SHA256:
- b65fb0c1d157d4069c25186ee6c05d66570179ea0338e2552e94b5f707d6255e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.