Instructions to use tweettemposhift/hate-hate_random2_seed1-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_random2_seed1-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_random2_seed1-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_random2_seed1-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_random2_seed1-bernice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd69c3729f7710f44f877fe512d15fb072cb23f7a9a1e37226736aa53298f53a
- Size of remote file:
- 4.54 kB
- SHA256:
- feeea563acb0a0783cbf00316e0f5668ca62281a3c50e9b5b2b84fdc49a6838c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.