Text Classification
Transformers
Safetensors
English
bert
finance
multi-label
optuna
classification
social-science
communication-science
Instructions to use nurdyansa/framing-bert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nurdyansa/framing-bert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nurdyansa/framing-bert-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nurdyansa/framing-bert-model") model = AutoModelForSequenceClassification.from_pretrained("nurdyansa/framing-bert-model") - Notebooks
- Google Colab
- Kaggle
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README.md
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- **Developed by:** Nurdyansa
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- **Model type:** BERT-based text classification model
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- **Language(s):** English
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- **License:**
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- **Finetuned from model:** `bert-base-uncased`
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### Model Sources
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- **Developed by:** Nurdyansa
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- **Model type:** BERT-based text classification model
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- **Language(s):** English
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- **License:** MIT
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- **Finetuned from model:** `bert-base-uncased`
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### Model Sources
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