Instructions to use Social-Media-Fairness/td1_test_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Social-Media-Fairness/td1_test_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Social-Media-Fairness/td1_test_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Social-Media-Fairness/td1_test_classifier") model = AutoModelForSequenceClassification.from_pretrained("Social-Media-Fairness/td1_test_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Social-Media-Fairness/td1_test_classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Social-Media-Fairness/td1_test_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Social-Media-Fairness/td1_test_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Social-Media-Fairness/td1_test_classifier/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 9e7b97a489c807775de83d17d6f77ffb0e9f6dc8a54f57b9f98f8968994651fb
- Size of remote file:
- 438 MB
- SHA256:
- 242af7a6dce403fda91cd64a15531c30aaab235d275e13869829047af254d5d2
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