Instructions to use ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32")# Load model directly from transformers import AutoTokenizer, DistilBertForMulticlassSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32") model = DistilBertForMulticlassSequenceClassification.from_pretrained("ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
π© Report : Legal issue(s)
#1
by ongkn - opened
Hello!
We'd like to add our own license to the list of selectable licenses. Is this something that you could do?
The license is outlined here:
https://ai.ongakken.com/ongakkenai-ml-license-v1-0/
Thanks
Hello! You can pick the license 'other' and have your own in the repo.
ongkn changed discussion status to closed