Instructions to use ibm-research/ColD-Fusion-itr13-seed2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/ColD-Fusion-itr13-seed2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ibm-research/ColD-Fusion-itr13-seed2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ibm-research/ColD-Fusion-itr13-seed2") model = AutoModelForSequenceClassification.from_pretrained("ibm-research/ColD-Fusion-itr13-seed2") - Notebooks
- Google Colab
- Kaggle
We find your model to be a great base-model
#4
by eladven - opened
We find your model to be the 1th best base model over roberta-base architecture.
(Means that using your model as a starting point for finetuning is great)
We suggest to add the following Evaluation to your README.md page.
For any question please contact eladv@il.ibm.com
eladven changed pull request status to closed