Instructions to use dongboklee/dORM-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dongboklee/dORM-14B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dongboklee/dORM-14B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dongboklee/dORM-14B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dongboklee/dORM-14B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/dongboklee/dORM-14B/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://dongboklee/dORM-14B@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/dongboklee/dORM-14B/resolve/refs%2Fpr%2F1/tokenizer.json
11.4 MB
- Xet hash:
- 78af695675c4fc8453e45a039d33450bec835340edcdac08f9a1af71f046ab0d
- Size of remote file:
- 11.4 MB
- SHA256:
- e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.