Text Classification
Transformers
Safetensors
English
bert
proposal-analysis
business
binary-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use JonahDelman/ProposalClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonahDelman/ProposalClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JonahDelman/ProposalClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JonahDelman/ProposalClassifier") model = AutoModelForSequenceClassification.from_pretrained("JonahDelman/ProposalClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13ed398f60d0303dfb35b81f32621a5ee3e8a1a55775b188210efc60041361a6
- Size of remote file:
- 438 MB
- SHA256:
- 105100d10056f0c7b5d632f44c55bf20950be546c05f7c4aef172903392b2096
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