Text Classification
Transformers
Safetensors
bert
l5
repository-library
repository_library_search_stack
research-library
span-infill-gate
text-embeddings-inference
Instructions to use PeytonT/span-infill-gate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PeytonT/span-infill-gate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PeytonT/span-infill-gate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PeytonT/span-infill-gate") model = AutoModelForSequenceClassification.from_pretrained("PeytonT/span-infill-gate") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8d394a849a3805e591be666c79c605e26f7afb2593884edea2e730e681b0366
- Size of remote file:
- 5.78 kB
- SHA256:
- c77dc18f4269c8f510ebf9022db6486735c84d5864ed18d452deb9a5f308d29d
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