Instructions to use tweettemposhift/hate-hate_random3_seed2-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_random3_seed2-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_random3_seed2-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_random3_seed2-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_random3_seed2-bernice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0aab5948288fda93dddaca9b2f2fec1fb7274697a61c4ee4200eb525c584a242
- Size of remote file:
- 4.54 kB
- SHA256:
- 87fdcd00521e520a81f432d7466f785ad16da257692bb5f629dde3f35afc8485
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.