Instructions to use UVA-MSBA/Mod4_T7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UVA-MSBA/Mod4_T7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UVA-MSBA/Mod4_T7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UVA-MSBA/Mod4_T7") model = AutoModelForSequenceClassification.from_pretrained("UVA-MSBA/Mod4_T7") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 18231a3
Upload BertForSequenceClassification
Browse files- config.json +1 -1
config.json
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{
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"_name_or_path": "/project/msbada3-23/team7/base_model
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"architectures": [
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"BertForSequenceClassification"
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],
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{
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"_name_or_path": "/project/msbada3-23/team7/base_model",
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"architectures": [
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"BertForSequenceClassification"
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],
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