Instructions to use tweettemposhift/hate-hate_random2_seed2-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_random2_seed2-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_random2_seed2-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_random2_seed2-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_random2_seed2-bernice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28a37977975b635a82d7b07a62f2a0a913261f72b5d83e123827dd4d33118be5
- Size of remote file:
- 1.11 GB
- SHA256:
- 47342abc7ba01a89a20e06793f34a5989067ba87f00fecd3f9ff4df76cc6ef8a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.