Text Classification
Transformers
ONNX
Safetensors
Transformers.js
English
distilbert
finance
transactions
english
text-embeddings-inference
Instructions to use DoDataThings/distilbert-us-transaction-classifier-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DoDataThings/distilbert-us-transaction-classifier-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DoDataThings/distilbert-us-transaction-classifier-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DoDataThings/distilbert-us-transaction-classifier-v2") model = AutoModelForSequenceClassification.from_pretrained("DoDataThings/distilbert-us-transaction-classifier-v2") - Transformers.js
How to use DoDataThings/distilbert-us-transaction-classifier-v2 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'DoDataThings/distilbert-us-transaction-classifier-v2'); - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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@@ -31,10 +31,10 @@ The model takes a sign prefix + transaction description and outputs one of 17 ca
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Input: "[debit] STARBUCKS #1234 SAN FRANCISCO CA"
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Output: Restaurants (0.99)
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Input: "[credit]
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Output: Income (1.00)
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Input: "[debit] CHASE CREDIT CRD AUTOPAY PPD ID:
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Output: Transfer (1.00)
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Input: "[debit] PreApproved Payment Bill User Payment: Netflix"
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Input: "[debit] STARBUCKS #1234 SAN FRANCISCO CA"
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Output: Restaurants (0.99)
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Input: "[credit] ACME CORP PAYROLL PPD ID: 123456789"
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Output: Income (1.00)
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Input: "[debit] CHASE CREDIT CRD AUTOPAY PPD ID: 9876543210"
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Output: Transfer (1.00)
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Input: "[debit] PreApproved Payment Bill User Payment: Netflix"
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