Instructions to use tweettemposhift/hate-hate_random3_seed1-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_random3_seed1-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_random3_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_random3_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_random3_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 274a669aa0f61983866576d540a1c35f915b5946e5d8ce191f3eb24b1a686022
- Size of remote file:
- 4.54 kB
- SHA256:
- c955c298acef37788a9f7ebdd81fe5ec8cd39a27ce611d90dd47ed712b0222fa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.