Instructions to use Jtisch7/bertFinancialSent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jtisch7/bertFinancialSent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jtisch7/bertFinancialSent")# Load model directly from transformers import AutoTokenizer, TF_AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jtisch7/bertFinancialSent") model = TF_AutoModelForSequenceClassification.from_pretrained("Jtisch7/bertFinancialSent") - Notebooks
- Google Colab
- Kaggle
Merge branch 'main' of https://huggingface.co/Jtisch7/bertFinancialSent
Browse files- config.json +1 -1
config.json
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{
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"_name_or_path": "bert-base-cased",
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"architectures": [
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"
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],
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"attention_probs_dropout_prob": 0.1,
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"gradient_checkpointing": false,
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{
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"_name_or_path": "bert-base-cased",
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"architectures": [
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"TFBertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"gradient_checkpointing": false,
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