Text Classification
Transformers
Safetensors
edlm
feature-extraction
decision-model
system-one
custom_code
Instructions to use nace-ai/drex-dlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nace-ai/drex-dlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nace-ai/drex-dlm", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nace-ai/drex-dlm", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download examples/request.json from nace-ai/drex-dlm: direct link, hf CLI and curl.
- Browser
- Download file 680 Bytes
-
https://huggingface.co/nace-ai/drex-dlm/resolve/main/examples/request.json
- Command line
-
hf download hf://nace-ai/drex-dlm/examples/request.json
-
curl -L -o request.json https://huggingface.co/nace-ai/drex-dlm/resolve/main/examples/request.json
680 Bytes
| { | |
| "model": "drex-dlm", | |
| "state": { | |
| "ticket": "I was charged twice for the same order. Please refund the extra payment." | |
| }, | |
| "questions": { | |
| "team": { | |
| "type": "choice", | |
| "instructions": "Which team should handle this ticket?", | |
| "criteria": { | |
| "billing": "Payments, charges, and refunds", | |
| "technical": "Bugs and outages", | |
| "other": "Anything else" | |
| } | |
| }, | |
| "refund": { | |
| "type": "noul", | |
| "instructions": "Does the customer explicitly ask for a refund?" | |
| }, | |
| "urgency": { | |
| "type": "score", | |
| "instructions": "How urgent is this ticket?", | |
| "criteria": ["Routine", "Soon", "Urgent"] | |
| } | |
| } | |
| } | |