Instructions to use coggpt/column_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coggpt/column_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="coggpt/column_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("coggpt/column_model") model = AutoModelForSequenceClassification.from_pretrained("coggpt/column_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66c99a1edb1234a52e948ea693a6beb0121e453d38a2ce0cac867d91145a0188
- Size of remote file:
- 268 MB
- SHA256:
- 34d7c133283b0861162ebc14697e3557f095502ad7d0fc412634b592ab553e77
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