Instructions to use tweettemposhift/topic-topic_random3_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_random3_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_random3_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random3_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random3_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b38fad44162443c99cf9d3ee3298c705e91ecedf576b04e4e233c34bb0eba20
- Size of remote file:
- 499 MB
- SHA256:
- 413aee21744d4908d8d9f5431f0e67e85a9b46f80e07191a9bda5ef139022e10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.