Text Classification
Transformers
Safetensors
edlm
feature-extraction
decision-model
system-one
typed-decisions
decision-index
classification
calibrated-probabilities
decisionbench
zero-shot
recommendation
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 assets/drex-dlm-architecture.png from nace-ai/drex-dlm: direct link, hf CLI and curl.
- Browser
- Download file 1.56 MB
-
https://huggingface.co/nace-ai/drex-dlm/resolve/main/assets/drex-dlm-architecture.png
- Command line
-
hf download hf://nace-ai/drex-dlm/assets/drex-dlm-architecture.png
-
curl -L -o drex-dlm-architecture.png https://huggingface.co/nace-ai/drex-dlm/resolve/main/assets/drex-dlm-architecture.png
1.56 MB

- Xet hash:
- 7b24cc9ff9afc4e514648203889002c9171299fdb1373a45107680642f136a46
- Size of remote file:
- 1.56 MB
- SHA256:
- 74bfd443bc78cf1c9627c45abe4814d606c352cebfaa1220b5d22d53e26504ce
·
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