Instructions to use LittleFish-Coder/gossipcop_pseudo_labeler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LittleFish-Coder/gossipcop_pseudo_labeler with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LittleFish-Coder/gossipcop_pseudo_labeler")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LittleFish-Coder/gossipcop_pseudo_labeler") model = AutoModelForSequenceClassification.from_pretrained("LittleFish-Coder/gossipcop_pseudo_labeler", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 570f1255418ea0624ed655790f6c2e9460707e12bb28d217c87f99f813dd6f4f
- Size of remote file:
- 268 MB
- SHA256:
- bcc0a0a398e27df18253a34eaeb5c668e4bdb052df2a6ae1e425175e97f41b1e
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