Instructions to use tweettemposhift/hate-hate_balance_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_balance_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_balance_random3_seed2-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_balance_random3_seed2-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_balance_random3_seed2-bernice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tweettemposhift/hate-hate_balance_random3_seed2-bernice: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/tweettemposhift/hate-hate_balance_random3_seed2-bernice/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tweettemposhift/hate-hate_balance_random3_seed2-bernice/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tweettemposhift/hate-hate_balance_random3_seed2-bernice/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- e64a514313a480599f42fa8fda7bb1c0e2d1c9db073e40e9a6ff110e18283400
- Size of remote file:
- 1.11 GB
- SHA256:
- 8fc26a8cbac52bb74fb3c9bec66828975a5bf53c77408963cdf97d1052f82692
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.