Text Classification
Transformers
Safetensors
bert
synthetic-data
document-ai
business-document-agents
workflow-routing
agent-evaluation
text-embeddings-inference
Instructions to use xdanielsb/doc-oracle-bert-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xdanielsb/doc-oracle-bert-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xdanielsb/doc-oracle-bert-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xdanielsb/doc-oracle-bert-v1") model = AutoModelForSequenceClassification.from_pretrained("xdanielsb/doc-oracle-bert-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "label2id": { | |
| "auto_approve": 0, | |
| "draft_created": 2, | |
| "draft_quote": 3, | |
| "human_review": 1 | |
| }, | |
| "labels": [ | |
| "auto_approve", | |
| "human_review", | |
| "draft_created", | |
| "draft_quote" | |
| ] | |
| } |