Instructions to use tcepi/type_object_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tcepi/type_object_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tcepi/type_object_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tcepi/type_object_model") model = AutoModelForSequenceClassification.from_pretrained("tcepi/type_object_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e70bc5193e67b389f81c7aa541e012ac15d1d6366ad01569f8dabe929a48898
- Size of remote file:
- 436 MB
- SHA256:
- 4e49f8dc5e10c983650fbdfd13498a288903d8a622a960d7a96fdac53ce5f410
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