Instructions to use tweettemposhift/topic-topic_random1_seed1-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random1_seed1-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random1_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random1_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random1_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9fcc7f40b1c2c034362620ca5c5c7226c9fabdb0323a134186a3fd604f2a5d8
- Size of remote file:
- 4.54 kB
- SHA256:
- 628c2d85ce6dbed07c2348d06e65d49112040bd36c016729e12c9bafb476a922
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.