Instructions to use qc7/shad_ml2_transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qc7/shad_ml2_transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="qc7/shad_ml2_transformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("qc7/shad_ml2_transformer") model = AutoModelForSequenceClassification.from_pretrained("qc7/shad_ml2_transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add requirements (trans, torch, pd)
Browse files- requirements.txt +4 -0
requirements.txt
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torch
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torchvision
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transformers
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pandas
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