Text Classification
Transformers
Safetensors
English
roberta
sequence-classification
erpnext
doctype-classification
text-embeddings-inference
Instructions to use hyrinmansoor/text2frappe-s1-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyrinmansoor/text2frappe-s1-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hyrinmansoor/text2frappe-s1-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hyrinmansoor/text2frappe-s1-roberta") model = AutoModelForSequenceClassification.from_pretrained("hyrinmansoor/text2frappe-s1-roberta") - Notebooks
- Google Colab
- Kaggle
π€ text2frappe-s1: Doctype Classifier (RoBERTa)
This model classifies ERP-style business questions into the correct ERPNext Doctype. It is the first stage of the ChangAI pipeline.
- Model Type: RoBERTa-base fine-tuned
- Use Case: Predicts ERPNext Doctype from user question
- Stage: S1 - Doctype Classification
π Example Input
"Where can I view all active sales invoices?"
β Example Output
Sales Invoice
Trained by @hyrinmansoor on real ERP-style data.
- Downloads last month
- -