Instructions to use aydippy/dippy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aydippy/dippy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aydippy/dippy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aydippy/dippy") model = AutoModelForSequenceClassification.from_pretrained("aydippy/dippy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- config.json +2 -2
config.json
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"finetuning_task": "sst-2",
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"hidden_dim": 3072,
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"id2label": {
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"initializer_range": 0.02,
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"label2id": {
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"finetuning_task": "sst-2",
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"hidden_dim": 3072,
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"id2label": {
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"0": "not_entailment",
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"1": "entailment"
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},
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"initializer_range": 0.02,
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"label2id": {
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