Instructions to use aekupor/connecting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aekupor/connecting with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aekupor/connecting")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aekupor/connecting") model = AutoModelForSequenceClassification.from_pretrained("aekupor/connecting", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01debe218c05fcd9fe2bd0e36b7255a82fba0f07b1dd8ba40736e166f90625ce
- Size of remote file:
- 499 MB
- SHA256:
- cbb13cc66ca8a6202d9de0c2f7f7e060d79764bfe005a269ef31074120544e15
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