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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PeytonT/span-infill-gate") model = AutoModelForSequenceClassification.from_pretrained("PeytonT/span-infill-gate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PeytonT/span-infill-gate: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/PeytonT/span-infill-gate/resolve/main/tokenizer.json
- Command line
-
hf download hf://PeytonT/span-infill-gate/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/PeytonT/span-infill-gate/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.